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JPL C Coding Standard [pdf]

1 September 2015 - 11:31pm

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Everything You Need to Know to Write Good C Code

1 September 2015 - 9:56pm
stronglink/SUBSTANCE.md at master · btrask/stronglink · GitHub

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To Stop Procrastinating, Start by Understanding the Emotions Involved

1 September 2015 - 6:29pm
Updated Aug. 31, 2015 11:44 p.m. ET

Putting off a work or school assignment in order to play videogames or water the plants might seem like nothing more serious than poor time-management.

But researchers say chronic procrastination is an emotional strategy for dealing with stress, and it can lead to significant issues in relationships, jobs, finances and health.

In August, researchers from Stockholm University published one of the first randomized controlled trials on the treatment of procrastination. It found a therapy delivered online can significantly reduce procrastination.

Psychologists also are studying other ways people might be able to reduce procrastination, such as better emotion-regulation strategies and visions of the future self.

Scientists define procrastination as the voluntary delay of an action despite foreseeable negative future consequences. It is opting for short-term pleasure or mood at the cost of the long-term. Perhaps we didn’t finish preparing a presentation on the weekend because we had house guests. That is just intentional delay based on a rational decision, says Timothy Pychyl (pronounced pitch-el), a psychology professor at Carleton University, in Ottawa, who has published extensively on the topic.

The essence of procrastination is “we’re giving in to feel good,” Dr. Pychyl says. “Procrastination is, ‘I know I should be doing it, I want to, it gets under my skin [when I don’t].’ ”

Ben Lockwood, a 39-year-old office manager in Chippenham, about 100 miles west of London, knows the feeling all too well. Even though he isn’t a lazy person, he says, he struggles with procrastination at work and in his personal life. He says he feels paralyzed by wanting to do everything perfectly, which then makes him feel anxious about getting started.

Instead of looking for a new job, he might go to the gym—a move researchers call “moral compensation.” That is when procrastinators do something to make themselves feel good or productive in order to avoid the task that needs to get done.

Mr. Lockwood says this pattern of behavior fills him with self-loathing. “I think I’d rather tell someone I robbed a bank than tell them I procrastinate,” he says.

Chronic procrastinators often hold misconceptions about why they procrastinate and what it means, psychologists have discovered. Many chronic procrastinators believe they can’t get started on a task because they want to do it perfectly. Yet studies show chronic procrastination isn’t actually linked to perfectionism, but rather to impulsiveness, which is a tendency to act immediately on urges, according to Piers Steel, an organizational-behavior professor at the University of Calgary.

To Procrastinate Less, Start by Doing This

Tips from research led by Timothy Pychyl, Piers Steel and Alexander Rozental.

  • Break a long-term project down into specific sub-goals. State the exact start time and how long (not just “tomorrow”) you plan to work on the task.
  • Just get started. It isn’t necessary to write a long list of tasks, or each intermediate step.
  • Remind yourself that finishing the task now helps you in the future. Putting off the task won’t make it more enjoyable.
  • Implement “microcosts,” or mini-delays, that require you to make a small effort to procrastinate, such as having to log on to a separate computer account for games.
  • Reward yourself not only for completing the entire project but also the sub-goals.

People may assume anxiety is what prevents them from getting started, yet data from many studies show that for people low in impulsiveness, anxiety is the cue to get going. Highly impulsive people, on the other hand, shut down when they feel anxiety. Impulsive people are believed to have a harder time dealing with strong emotion and want to do something else to get rid of the bad feeling, Dr. Steel says.

Some people claim they purposely leave things to the last minute because they work better under stress, but true procrastinators get stressed out by the delay. It’s arguable whether the quality of their work is actually better than if they had started earlier, according to Dr. Pychyl.

Experts say the consequences of chronic or extreme procrastination can be serious: Marriages break up, people lose jobs and often feel like impostors. Fuschia Sirois, a psychology professor at the University of Sheffield, in England, recently began studying the effects of procrastination on coping with chronic illness.

The mental-health effects of procrastination are well-documented: Habitual procrastinators have higher rates of depression and anxiety and poorer well-being.

Less is known about physical effects, and especially serious health problems. In a recent paper, Dr. Sirois and colleagues found procrastinators with hypertension and heart disease were less likely to engage in active strategies for coping with the illness, such as finding meaning or taking action, such as arranging to exercise with a friend. They were more likely to adopt maladaptive behaviors, like being avoidant or blaming themselves for the illness and trying to forget it.

In addition, procrastinators often seem unable to see as clearly into the future about their choices and behaviors as non-procrastinators—a phenomenon she calls “temporal myopia.” Their vision of their future selves is often more abstract and impersonal, and they’re less connected emotionally to their future selves. Temporal myopia may be largely due to their high levels of stress which can shift their focus to more immediate rather than distant concerns.

“A lot of us think, I’m doing it for me” and that in the future we’ll benefit because of what we’re doing now, says Dr. Sirois. But procrastinators aren’t as good at envisioning this. Dr. Sirois, Carleton’s Dr. Pychyl and others are testing interventions for helping procrastinators better envision and connect with their future selves.

Focusing on time management alone will help procrastinators, but only so much, the scientists say. The emotional regulation component must be addressed as well.

Dr. Sirois and Dr. Pychyl also have focused on short-term mood repair as an anti-procrastination strategy. They teach people to recognize that they might have strong emotions, such as anxiety, at the start of a project but to not judge themselves for it. The next step is just to get started, step by step, with a narrow focus.

At Stockholm University, researchers set out to test whether a self-help treatment could have an effect on more-severe forms of procrastination, as the research in this area was lacking. Though there are many self-help books and experimental lab studies, the group wanted to design an intervention that, if shown efficacious, could be rolled out widely, such as via the Internet, said Alexander Rozental, a clinical psychologist and doctoral student who was an author of the study, which was recently published in the Journal of Consulting and Clinical Psychology.

Some 150 participants were self-reported high procrastinators and were randomly assigned to complete the intervention, either by themselves, with the guidance of a therapist or to a wait-list control. The treatment program consisted of 10 weekly modules.

One component focused on goal setting, such as breaking down long-term goals into smaller and more-concrete sub-goals. Instead of saying one was going to work on a paper on Tuesday, participants were taught to be specific and divide it into manageable sub-goals: I am going to work on a paper for one hour at 11 a.m.

The intervention also employed a reward system. Participants would give themselves something positive, whether a cup of coffee or a break after accomplishing mini-goals, rather than wait until finishing the overall goal.

Another module involved exposing procrastinators to stressful feelings or thoughts in brief but gradually longer periods. The goal there is to help them feel that they are better able to manage their emotions and not to instinctively follow them.

The results showed that after intervention with both guided and unguided self-help, people improved their procrastination, though the guided therapy seemed to show greater benefit. The researchers, who have continued following up with the participants, will look at one-year outcomes later this year to see if the results were maintained.

They also are conducting a study of college students receiving either group therapy or Internet-based cognitive behavior therapy, where they will look not only at self-reported procrastination but also at real-life outcomes including academic grades and use of alcohol and drugs, Mr. Rozental says.

In Calgary, Dr. Steel’s lab is testing and helping to develop new software with a Hong Kong company, Saent, that helps by delaying the loading of websites such as Facebook for 15 seconds or so, using “micro-costs” such as requiring a password before surfing the Web. Sometimes these little bits of effort are all that are necessary to deter procrastinators from distraction, Dr. Steel says.

Mr. Lockwood, the procrastinator from the U.K., has developed his own strategies for helping him delay tasks. Since he’s had to pay late fees before for not paying bills on time, for no reason other than he didn’t put the check in the mail, he now makes sure he’s always stocked with stamps and envelopes at home and has online bill pay set up for as many places as possible.

But he wishes he could shake his procrastination in other areas of his life. He says his girlfriend is always planning their vacations because he has a hard time getting started and is reluctant to ask for time off. But he actually enjoys the act of planning trips. He says one day he would love to surprise her by coming up with the idea and doing the planning.

“If you’re an occasional procrastinator, quit thinking about your feelings and get to the next task,” says Dr. Pychyl. “But if you’re a chronic procrastinator, you might need therapy to better understand your emotions and how you’re coping with them through avoidance.”

Write to Shirley S. Wang at shirley.wang@wsj.com

Google Will Soon Start Punishing Mobile Sites that Use Annoying App Install Ads

1 September 2015 - 4:25pm

There’s nothing wrong with app install ads, but too often now, you click on a mobile search result, and when the site loads, a giant app install interstitial pops up that prompts you to install that site’s app. Those ads typically block all the content on the site until you find that little small ‘x’ to click away the ad (and chances are you will mistakenly click next to it and basically click on the ad, which then takes you to Google Play). Thankfully, Google today announced that it will soon start downranking sites that do this.

According to an update to webmasters the company posted today, Google’s mobile-friendly test will now indicate when a site should avoid these kinds of app install interstitials. Starting November 1, sites that show app install ads that hide “a significant amount of content on the transition from the search result page” will be penalized by losing their “mobile-friendly” status. This means they will likely rank lower on Google’s mobile search results pages.

It’s worth noting that Google won’t punish sites that use the standard (and much smaller) app install banners in Chrome and Safari.

Giant app install interstitials have indeed become really annoying. When I click on a search result, chances are I want to see the content on the site — not install its mobile app.

You could argue that Google is obviously better at monetizing on the web than in mobile apps, so it wants people to stay in the browser, but these interstitials are simply an annoyance and I for one appreciate that Google is trying to do something about this.

Brazilian wasp venom kills cancer cells by opening them up

1 September 2015 - 3:34pm
Brazilian wasp venom kills cancer cells by opening them up September 1, 2015 Brazilain social wasp Polybia paulista. Credit: Prof. Mario Palma/Sao Paulo State University

The social wasp Polybia paulista protects itself against predators by producing venom known to contain a powerful cancer-fighting ingredient. A Biophysical Journal study published September 1 reveals exactly how the venom's toxin—called MP1 (Polybia-MP1)—selectively kills cancer cells without harming normal cells. MP1 interacts with lipids that are abnormally distributed on the surface of cancer cells, creating gaping holes that allow molecules crucial for cell function to leak out.

"Cancer therapies that attack the lipid composition of the cell membrane would be an entirely new class of anticancer drugs," says co-senior study author Paul Beales, of the University of Leeds in the UK. "This could be useful in developing new combination therapies, where multiple drugs are used simultaneously to treat a cancer by attacking different parts of the cancer cells at the same time."

MP1 acts against microbial pathogens by disrupting the bacterial cell membrane. Serendipitously, the antimicrobial peptide shows promise for protecting humans from cancer; it can inhibit the growth of prostate and bladder cancer cells, as well as multi-drug resistant leukemic cells. However, until now, it was not clear how MP1 selectively destroys cancer cells without harming .

Beales and co-senior study author João Ruggiero Neto of São Paulo State University in Brazil suspected that the reason might have something to do with the unique properties of cancer cell membranes. In healthy cell membranes, phospholipids called phosphatidylserine (PS) and phosphatidylethanolamine (PE) are located in the inner membrane leaflet facing the inside of the cell. But in cancer cells, PS and PE are embedded in the outer membrane leaflet facing the cell surroundings.

The researchers tested their theory by creating model membranes, some of which contained PE and/or PS, and exposing them to MP1. They used a wide range of imaging and biophysical techniques to characterize MP1's destructive effects on the membranes. Strikingly, the presence of PS increased the binding of MP1 to the membrane by a factor of 7 to 8. On the other hand, the presence of PE enhanced MP1's ability to quickly disrupt the membrane, increasing the size of holes by a factor of 20 to 30.

"Formed in only seconds, these large pores are big enough to allow critical molecules such as RNA and proteins to easily escape cells," Neto says. "The dramatic enhancement of the permeabilization induced by the peptide in the presence of PE and the dimensions of the pores in these membranes was surprising."

In future studies, the researchers plan to alter MP1's amino acid sequence to examine how the peptide's structure relates to its function and further improve the peptide's selectivity and potency for clinical purposes. "Understanding the mechanism of action of this peptide will help in translational studies to further assess the potential for this peptide to be used in medicine," Beales says. "As it has been shown to be selective to and non-toxic to normal cells in the lab, this peptide has the potential to be safe, but further work would be required to prove that."

Explore further: Nanofibers Carry Toxic Peptides Into Cancer Cells

More information: Biophysical Journal, Leite et al.: "PE and PS Lipids Synergistically Enhance Membrane Poration by a Host-Defense Peptide with Anticancer Properties" dx.doi.org/10.1016/j.bpj.2015.07.033

Journal reference: Biophysical Journal

Provided by: Cell Press

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Brazilian wasp venom kills cancer cells by opening them up September 1, 2015

Brazilain social wasp

Polybia paulista

. Credit: Prof. Mario Palma/Sao Paulo State University

The social wasp Polybia paulista protects itself against predators by producing venom known to contain a powerful cancer-fighting ingredient. A Biophysical Journal study published September 1 reveals exactly how the venom's toxin—called MP1 (Polybia-MP1)—selectively kills cancer cells without harming normal cells. MP1 interacts with lipids that are abnormally distributed on the surface of cancer cells, creating gaping holes that allow molecules crucial for cell function to leak out.

"Cancer therapies that attack the lipid composition of the cell membrane would be an entirely new class of anticancer drugs," says co-senior study author Paul Beales, of the University of Leeds in the UK. "This could be useful in developing new combination therapies, where multiple drugs are used simultaneously to treat a cancer by attacking different parts of the cancer cells at the same time."

MP1 acts against microbial pathogens by disrupting the bacterial cell membrane. Serendipitously, the antimicrobial peptide shows promise for protecting humans from cancer; it can inhibit the growth of prostate and bladder cancer cells, as well as multi-drug resistant leukemic cells. However, until now, it was not clear how MP1 selectively destroys cancer cells without harming .

Beales and co-senior study author João Ruggiero Neto of São Paulo State University in Brazil suspected that the reason might have something to do with the unique properties of cancer cell membranes. In healthy cell membranes, phospholipids called phosphatidylserine (PS) and phosphatidylethanolamine (PE) are located in the inner membrane leaflet facing the inside of the cell. But in cancer cells, PS and PE are embedded in the outer membrane leaflet facing the cell surroundings.

The researchers tested their theory by creating model membranes, some of which contained PE and/or PS, and exposing them to MP1. They used a wide range of imaging and biophysical techniques to characterize MP1's destructive effects on the membranes. Strikingly, the presence of PS increased the binding of MP1 to the membrane by a factor of 7 to 8. On the other hand, the presence of PE enhanced MP1's ability to quickly disrupt the membrane, increasing the size of holes by a factor of 20 to 30.

"Formed in only seconds, these large pores are big enough to allow critical molecules such as RNA and proteins to easily escape cells," Neto says. "The dramatic enhancement of the permeabilization induced by the peptide in the presence of PE and the dimensions of the pores in these membranes was surprising."

In future studies, the researchers plan to alter MP1's amino acid sequence to examine how the peptide's structure relates to its function and further improve the peptide's selectivity and potency for clinical purposes. "Understanding the mechanism of action of this peptide will help in translational studies to further assess the potential for this peptide to be used in medicine," Beales says. "As it has been shown to be selective to and non-toxic to normal cells in the lab, this peptide has the potential to be safe, but further work would be required to prove that."

Explore further: Nanofibers Carry Toxic Peptides Into Cancer Cells

More information: Biophysical Journal, Leite et al.: "PE and PS Lipids Synergistically Enhance Membrane Poration by a Host-Defense Peptide with Anticancer Properties" dx.doi.org/10.1016/j.bpj.2015.07.033

Journal reference: Biophysical Journal

Provided by: Cell Press

More from Chemistry

Related StoriesNanofibers Carry Toxic Peptides Into Cancer Cells April 22, 2010

(PhysOrg.com) -- Researchers have long known that certain peptides are capable of killing cells by inserting themselves into the cell membranes and disrupting normal membrane structure and function. Now, researchers at Northwestern ...

How an emerging anti-resistance antibiotic targets the bacterial membrane August 18, 2015

Scientists are planning for a future in which superbugs gain the upper hand against our current arsenal of antibiotics. One emerging class of drug candidates, called AMLPs (antimicrobial lipopeptides), shows promise, and ...

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Water heals a bioplastic September 1, 2015

A drop of water self-heals a multiphase polymer derived from the genetic code of squid ring teeth, which may someday extend the life of medical implants, fiber-optic cables and other hard to repair in place objects, according ...

Brazilian wasp venom kills cancer cells by opening them up September 1, 2015

The social wasp Polybia paulista protects itself against predators by producing venom known to contain a powerful cancer-fighting ingredient. A Biophysical Journal study published September 1 reveals exactly how the venom's ...

Naturally-occurring protein enables slower-melting ice cream August 31, 2015

(Phys.org)—Scientists have developed a slower-melting ice cream—consider the advantages the next time a hot summer day turns your child's cone with its dream-like mound of orange, vanilla and lemon swirls with chocolate ...

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Materials scientists seeking to encapsulate droplets of one fluid within another often use molecules like soap or micro- or nano-particles to do it. One distinct way of wrapping a droplet is to use a thin sheet that calls ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here

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Evolving the Google Identity

1 September 2015 - 12:05pm

Google is not a conventional company. Our mission—to take the world’s information and make it universally accessible and useful—continues to evolve. Last year we introduced Material Design to help designers and developers embrace an expanding, multi-device, multi-screen world. With those considerations in mind, we are excited to share a new brand identity that aims to make Google more accessible and useful to our users—wherever they may encounter it.

Since its inception, the Google.com homepage has been strikingly simple: The quirky, multicolored logo sits above a single, approachable input field on a clean white canvas. But as technology moves forward, the canvas itself is changing, and the inputs and needs are becoming more diverse. New classes of devices and ways to interact and communicate have emerged with wearables, voice technology, and smart devices in the world around us. Users now engage with Google using a constellation of devices, and our brand should express the same simplicity and delight they expect from our homepage, while fully embracing the opportunities offered by each new device and surface.

Here’s a glimpse at some of the design considerations that went into taking the best of what people know and love about Google, and evolving the brand to continue to be as dynamic and unconventional as we strive to be.

Designed together

Early this year, designers from all across the company, including Creative Lab and the Material Design team, convened in New York for an intense, week-long design sprint. We drafted a brief that identified four challenges we wanted to address:

  1. A scalable mark that could convey the feeling of the full logotype in constrained spaces.

  2. The incorporation of dynamic, intelligent motion that responded to users at all stages of an interaction.

  3. A systematic approach to branding in our products to provide consistency in people’s daily encounters with Google.

  4. A refinement of what makes us Googley, combining the best of the brand our users know and love with thoughtful consideration for how their needs are changing.

We started by distilling the essence of our brand down to its core—four colors on a clean white background—and built it back up. Stickies were stuck, pins were pushed, and beziers were animated. With the cutting room floor littered with hundreds of hours of design work, we set out with a few directions that excited us.

We shared the thinking with teams across the organization. Engineering, research, product, and marketing tested the ideas and evaluated their feasibility as we iterated on the design and rollout strategy. This collaborative process led to a system flexible enough to be used across our marketing materials and product work on any platform: three elemental states that make up a single logo.

The Elements Google Logotype

A sans serif logotype that retains our distinct multi-color sequence.

Dots

A dynamic distillation of the logotype for interactive, assistive, and transitional moments.

Google G

A compact version of the Google logo that works in small contexts.

Understanding the system

The thinking and design development goes much deeper than the core elements, and a spec was developed to help with consistency across teams working on a wide range of applications. The following examples are not comprehensive, but show a bit of the thinking that went into the system.

Logotype

The Google logo has always had a simple, friendly, and approachable style. We wanted to retain these qualities by combining the mathematical purity of geometric forms with the childlike simplicity of schoolbook letter printing. Our new logotype is set in a custom, geometric sans-serif typeface and maintains the multi-colored playfulness and rotated ‘e’ of our previous mark—a reminder that we’ll always be a bit unconventional.

The final logotype was tested exhaustively at various sizes and weights for maximum legibility in all the new digital contexts. To guide usage in screen and print, we developed standards to cover all aspects of the logotype including spacing, clearance rules, product lockups, and redline specifications for in-product treatments.

Google G Construction

The Google G is directly derived from the logotype ‘G,’ but uses increased visual weight to stand up at small sizes and contexts where it needs to share space with other elements. Designed on the same grid as our product iconography, the circular shape was optically refined to prevent a visual “overbite” at the point where the circular form meets the crossbar. The color proportions convey the full spectrum of the logotype and are sequenced to aid eye movement around the letterform.

Google Dots in Motion

The Google dots are a dynamic and perpetually moving state of the logo. They represent Google’s intelligence at work and indicate when Google is working for you. We consider these unique, magic moments. A full range of expressions were developed including listening, thinking, replying, incomprehension, and confirmation. While their movements might seem spontaneous, their motion is rooted in consistent paths and timing, with the dots moving along geometric arcs and following a standard set of snappy easing curves.

Color

The Google logotype benefits from whitespace between letterforms, but when colors are adjacent—as in the case of the Google G—they optically blend and can result in a darkening and dimming of the original value. We adjusted and pushed the vibrancy of the red, green, and yellow to maintain saturation and pop.

Implementation Typography

In tandem with developing the logotype, we created a custom, geometric sans-serif typeface to complement the logo in product lockups and supporting identity materials. We call it Product Sans. The typeface design takes cues from that same schoolbook letter-printing style, but adopts the neutral consistency we’ve all come to expect from a geometric sans serif. This allows us to maintain an appropriate level of distinction between the Google logotype and the product name. The character set is complete with numerals, punctuation, accent and alternate characters, fractions, symbols, and supports extended Latin, Greek, and Cyrillic.

Product

Many of our products across Google will be releasing the update, but for most people, the very first experience of the new brand will be through Search. The Search UX and engineering teams worked hard to deliver the first embodiment of the text and voice queries, demonstrating the identity’s full range of expression.

Broader distribution

As the design evolved, engineering developed a unique approach for asset generation, version control, and self-service distribution across our code base. Using pixel-perfect SVGs for base assets, we automatically generated thousands of vector-based variants to satisfy size, color, and background requirements. These variants are then checked into our source control in a canonical location to avoid duplication and ensure that every team is using the most correct, up-to-date assets.

This helps us make the design pixel perfect everywhere it’s used, and it allows us to optimize these assets for size and latency, including building a special variant of our full-color logo that is only 305 bytes, compared to our existing logo at ~14,000 bytes. The old logo, with its intricate serifs and larger file size, required that we serve a text-based approximation of the logo for low bandwidth connections. The new logo’s reduced file size avoids this workaround and the consistency has tremendous impact when you consider our goal of making Google more accessible and useful to users around the world, including the next billion.

Beyond design

Design was only one part of the effort. The realization of the new identity required the collective work and diligence of hundreds of Googlers, in different roles, spanning the entire organization. They deserve huge credit for building and implementing the system down to the very last pixel.

As we move forward creating new products and experiences, we hope this work will continue to deliver the simplicity and delight you expect from Google—wherever new technology may take us.

 

Google’s look, evolved

1 September 2015 - 11:44am

This isn’t the first time we’ve changed our look and it probably won’t be the last, but we think today’s update is a great reflection of all the ways Google works for you across Search, Maps, Gmail, Chrome and many others. We think we’ve taken the best of Google (simple, uncluttered, colorful, friendly), and recast it not just for the Google of today, but for the Google of the future.

You’ll see the new design roll out across our products soon. Hope you enjoy it!

Posted by Tamar Yehoshua, VP, Product Management & Bobby Nath, Director of User Experience

Google has changed a lot over the past 17 years—from the range of our products to the evolution of their look and feel. And today we’re changing things up once again.

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Google has changed a lot over the past 17 years—from the range of our products to the evolution of their look and feel. And today we’re changing things up once again:

So why are we doing this now? Once upon a time, Google was one destination that you reached from one device: a desktop PC. These days, people interact with Google products across many different platforms, apps and devices—sometimes all in a single day. You expect Google to help you whenever and wherever you need it, whether it’s on your mobile phone, TV, watch, the dashboard in your car, and yes, even a desktop!

Today we’re introducing a new logo and identity family that reflects this reality and shows you when the Google magic is working for you, even on the tiniest screens. As you’ll see, we’ve taken the Google logo and branding, which were originally built for a single desktop browser page, and updated them for a world of seamless computing across an endless number of devices and different kinds of inputs (such as tap, type and talk).

It doesn’t simply tell you that you’re using Google, but also shows you how Google is working for you. For example, new elements like a colorful Google mic help you identify and interact with Google whether you’re talking, tapping or typing. Meanwhile, we’re bidding adieu to the little blue “g” icon and replacing it with a four-color “G” that matches the logo.


This isn’t the first time we’ve changed our look and it probably won’t be the last, but we think today’s update is a great reflection of all the ways Google works for you across Search, Maps, Gmail, Chrome and many others. We think we’ve taken the best of Google (simple, uncluttered, colorful, friendly), and recast it not just for the Google of today, but for the Google of the future.

You’ll see the new design roll out across our products soon. Hope you enjoy it!

Posted by Tamar Yehoshua, VP, Product Management & Bobby Nath, Director of User Experience

Google has changed a lot over the past 17 years—from the range of our products to the evolution of their look and feel. And today we’re changing things up once again.

Forging an Alliance for Royalty-Free Video

1 September 2015 - 11:12am
Mozilla

Sep 1 2015

Things are moving fast for royalty-free video codecs. A month ago, the IETF NETVC Working Group had its first meeting and two weeks ago Cisco announced Thor. Today, we’re taking the next big step in this industry-wide effort with the formation of the Alliance for Open Media. Its founding members represent some of the biggest names in online video, such as Netflix, Amazon, and YouTube, multiple browser vendors including Mozilla, Microsoft, and Google, and key technology providers like Cisco and Intel. The Alliance has come together to share technology and run the kind of patent analysis necessary to build a next-generation royalty-free video codec.

Mozilla has long championed royalty-free codecs. The Web was built on innovation without asking permission, and patent licensing regimes are incompatible with some of the Web’s most successful business models. That’s why we already support great codecs like VP8, VP9, and Opus in Firefox. But the Web doesn’t stand still and neither do we. As resolutions and framerates increase, the need for more advanced codecs with ever-better compression ratios will only grow. We started our own Daala project and formed NETVC to meet those needs, and we’ve seen explosive interest in the result. We believe that Daala, Cisco’s Thor, and Google’s VP10 combine to form an excellent basis for a truly world-class royalty-free codec.

In order to allow us to move quickly, the alliance is structured as a Joint Development Foundation project. These are an ideal complement to a larger, open standards organization like the IETF: One of the biggest challenges in developing open standards in a field like video codecs is figuring out how to review the patents. The Alliance provides a venue for us to share the legal legwork without having to worry about it being used against us down the road. That distributes the load, allows us to innovate faster and cheaper, and gives everyone more confidence that we are really producing a royalty-free codec.

The Alliance will operate under W3C patent rules and release code under an Apache 2.0 license. This means all Alliance participants are waiving royalties both for the codec implementation and for any patents on the codec itself. The initial members are just a start. We invite anyone with an interest in video, online or off, to join us.

Categories: Mozilla News

Ask HN: Who is hiring? (September 2015)

1 September 2015 - 11:08am
Please lead with the location of the position and include the keywords REMOTE, INTERNS and/or VISA when the corresponding sort of candidate is welcome. When remote work is not an option, please include ONSITE.

Feel free to post any job that may interest HN readers from executive assistant to machine learning expert to CTO.

Please only post if you personally are part of the hiring company. No recruiting firms or job boards, please.

Stupid Patent of the Month: A Drink Mixer Attacks the Internet of Things

1 September 2015 - 10:43am

Imagine if the inventor of the Segway claimed to own “any thing that moves in response to human commands.” Or if the inventor of the telegraph applied for a patent covering any use of electric current for communication. Absurdly overbroad claims like these would not be allowed, right? Unfortunately, the Patent Office does not do a good job of policing overly broad claims. August's Stupid Patent of the Month, U.S. Patent No. 8,788,090, is a stark example of how these claims promote patent trolling.

A patent troll called Rothschild Connected Devices Innovations, LLC (“RCDI”) owns a family of patents on a system of customizing products. Each of these patents stems from the same 2006 application. The idea is simple: connect some kind of product mixer to the Internet and allow users to make custom orders. The application suggests using the system to make beverages or shampoo.

Here’s how the application describes the invention:

The system and method of the present disclosure enables a user, e.g., a consumer, to customize products containing solids and fluids by allowing a server communicating over the global computer network, e.g., the Internet, to provide product preferences of a user to a product or a mixing device, e.g., a product or beverage dispenser.

Even in 2006, this was a spectacularly mundane idea. The application did not disclose any new networking technology. Nor did it reveal any new beverage-making technology. It just connects a product mixer to the Internet. Any claim to such a humdrum combination should be found invalid as obvious.

All of the patents in this family are pretty silly. But it get worse. RCDI’s most recently granted patent, U.S. Patent No. 8,788,090, includes an extremely broad claim. Claim 1 purports to cover any system where a “remote server” “transmits” a “product preference” to a product via a “communication module.” This is madness. RCDI is effectively claiming to have invented the idea of remote configuration … in 2006. Even if other claims in this patent family are valid (something we doubt), the Patent Office should never have allowed this claim.

Taking an extremely broad view of this patent claim, RCDI has sued a collection of companies, including ADT, Cisco, Protect America, OnStar, and Rain Bird. It seems that any company that sells products that connect to the Internet is at risk. For example, in its complaint against ADT, RCDI states that a system that allows customers to “remotely customize the operation” of a “thermostat” infringes its patent. Having supposedly invented an online beverage mixer, RCDI is now asserting its patent against the entire Internet of Things.

Even though it traces priority back to a 2006 parent application, this month's stupid patent is not the product of some earlier, less diligent, era at the Patent Office. The “continuation” application that led to this patent was filed in March 2013 and the patent issued in July 2014. This illustrates how applicants use the continuation process (which allows them to file an unlimited number of new applications based on a previous patent application) to try to get ever broader claims issued. Too often, once the Patent Office issues one patent in a family, examiners are overly lenient allowing continuation applications. This month’s winner likely would have never issued if the examiner had diligently applied KSR v. Teleflex’s prohibition on obvious combinations.

There will be no prize for guessing where RCDI has filed all of its litigation: the Eastern District of Texas. We recently explained that the Eastern District is the venue of choice for trolls. Its unique, plaintiff-friendly rules make it easier for trolls to use the cost of defense to extort settlements, even when the underlying case is weak.

We need broad patent reform to stop abusive patent litigation. We need ligation reform (including venue reform) that makes patent trolling less attractive. We also need reform at the Patent Office so that it doesn’t issue terrible patents like this in the first place. Contact your representative and tell them to pass patent reform.

Happy personal news

1 September 2015 - 12:42am

With great happiness, Zack and I have some exciting news to share – I’m pregnant!  In fact, I’m expecting identical twin girls, likely arriving in December.  The twins part was quite a surprise, because I have no family history of twins or any other predisposing factors.  However, as I’ve now learned, identical twins occur by random chance in roughly 1 out of approximately every 300 pregnancies.  Zack and I have embraced the surprise and are very excited about these new additions to our family.  

Since my pregnancy has been healthy and uncomplicated and since this is a unique time in Yahoo’s transformation, I plan to approach the pregnancy and delivery as I did with my son three years ago, taking limited time away and working throughout.  I’ve shared the news and my plans with Yahoo’s Board of Directors and my executive team, and they are incredibly supportive and happy for me.  I want to thank them for all of their encouragement as well as their offers of help and continued support.

Leading Yahoo in our renaissance, alongside a terrific and dedicated team, has given me tremendous professional pride in our accomplishments.  I’ve never been more excited about our progress and the growth opportunities for our amazing company.  At the same time, I’m blessed to have experienced some of my most extraordinary and proudest personal moments while being Yahoo’s CEO.  Moving forward, there will be a lot to do for both my family and for Yahoo; both will require hard work and thoughtful prioritization.  However, I’m extremely energized by and dedicated to both my family and Yahoo and will do all that is necessary and more to help both thrive.  The future looks extremely bright on both fronts.

S3QL: an S3 FS with encryption, de-dup, immutable trees and snapshotting

1 September 2015 - 12:12am

S3QL is a file system that stores all its data online using storage services like Google Storage, Amazon S3, or OpenStack. S3QL effectively provides a hard disk of dynamic, infinite capacity that can be accessed from any computer with internet access running Linux, FreeBSD or OS-X.

S3QL is a standard conforming, full featured UNIX file system that is conceptually indistinguishable from any local file system. Furthermore, S3QL has additional features like compression, encryption, data de-duplication, immutable trees and snapshotting which make it especially suitable for online backup and archival.

S3QL is designed to favor simplicity and elegance over performance and feature-creep. Care has been taken to make the source code as readable and serviceable as possible. Solid error detection and error handling have been included from the very first line, and S3QL comes with extensive automated test cases for all its components.

Go GC: Prioritizing low latency and simplicity

31 August 2015 - 8:22pm
Go GC: Prioritizing low latency and simplicity

31 August 2015

The Setup

Go is building a garbage collector (GC) not only for 2015 but for 2025 and beyond: A GC that supports today’s software development and scales along with new software and hardware throughout the next decade. Such a future has no place for stop-the-world GC pauses, which have been an impediment to broader uses of safe and secure languages such as Go.

Go 1.5, the first glimpse of this future, achieves GC latencies well below the 10 millisecond goal we set a year ago. We presented some impressive numbers in a talk at Gophercon. The latency improvements have generated a lot of attention; Robin Verlangen’s blog post Billions of requests per day meet Go 1.5 validates our direction with end to end results. We also particularly enjoyed Alan Shreve’s production server graphs and his "Holy 85% reduction" comment.

Today 16 gigabytes of RAM costs $100 and CPUs come with many cores, each with multiple hardware threads. In a decade this hardware will seem quaint but the software being built in Go today will need to scale to meet expanding needs and the next big thing. Given that hardware will provide the power to increase throughput, Go’s garbage collector is being designed to favor low latency and tuning via only a single knob. Go 1.5 is the first big step down this path and these first steps will forever influence Go and the applications it best supports. This blog post gives a high-level overview of what we have done for the Go 1.5 collector.

The Embellishment

To create a garbage collector for the next decade, we turned to an algorithm from decades ago. Go's new garbage collector is a concurrent, tri-color, mark-sweep collector, an idea first proposed by Dijkstra in 1978. This is a deliberate divergence from most "enterprise" grade garbage collectors of today, and one that we believe is well suited to the properties of modern hardware and the latency requirements of modern software.

In a tri-color collector, every object is either white, grey, or black and we view the heap as a graph of connected objects. At the start of a GC cycle all objects are white. The GC visits all roots, which are objects directly accessible by the application such as globals and things on the stack, and colors these grey. The GC then chooses a grey object, blackens it, and then scans it for pointers to other objects. When this scan finds a pointer to a white object, it turns that object grey. This process repeats until there are no more grey objects. At this point, white objects are known to be unreachable and can be reused.

This all happens concurrently with the application, known as the mutator, changing pointers while the collector is running. Hence, the mutator must maintain the invariant that no black object points to a white object, lest the garbage collector lose track of an object installed in a part of the heap it has already visited. Maintaining this invariant is the job of the write barrier, which is a small function run by the mutator whenever a pointer in the heap is modified. Go’s write barrier colors the now-reachable object grey if it is currently white, ensuring that the garbage collector will eventually scan it for pointers.

Deciding when the job of finding all grey objects is done is subtle and can be expensive and complicated if we want to avoid blocking the mutators. To keep things simple Go 1.5 does as much work as it can concurrently and then briefly stops the world to inspect all potential sources of grey objects. Finding the sweet spot between the time needed for this final stop-the-world and the total amount of work that this GC does is a major deliverable for Go 1.6.

Of course the devil is in the details. When do we start a GC cycle? What metrics do we use to make that decision? How should the GC interact with the Go scheduler? How do we pause a mutator thread long enough to scan its stack?  How do we represent white, grey, and black so we can efficiently find and scan grey objects? How do we know where the roots are? How do we know where in an object pointers are located? How do we minimize memory fragmentation? How do we deal with cache performance issues? How big should the heap be? And on and on, some related to allocation, some to finding reachable objects, some related to scheduling, but many related to performance. Low-level discussions of each of these areas are beyond the scope of this blog post.

At a higher level, one approach to solving performance problems is to add GC knobs, one for each performance issue. The programmer can then turn the knobs in search of appropriate settings for their application. The downside is that after a decade with one or two new knobs each year you end up with the GC Knobs Turner Employment Act. Go is not going down that path. Instead we provide a single knob, called GOGC. This value controls the total size of the heap relative to the size of reachable objects. The default value of 100 means that total heap size is now 100% bigger than (i.e., twice) the size of the reachable objects after the last collection. 200 means total heap size is 200% bigger than (i.e., three times) the size of the reachable objects. If you want to lower the total time spent in GC, increase GOGC. If you want to trade more GC time for less memory, lower GOGC.

More importantly as RAM doubles with the next generation of hardware, simply doubling GOGC will halve the number of GC cycles. On the other hand since GOGC is based on reachable object size, doubling the load by doubling the reachable objects requires no retuning. The application just scales. Furthermore, unencumbered by ongoing support for dozens of knobs, the runtime team can focus on improving the runtime based on feedback from real customer applications.

The Punchline

Go 1.5’s GC ushers in a future where stop-the-world pauses are no longer a barrier to moving to a safe and secure language. It is a future where applications scale effortlessly along with hardware and as hardware becomes more powerful the GC will not be an impediment to better, more scalable software. It’s a good place to be for the next decade and beyond. For more details about the 1.5 GC and how we eliminated latency issues see the Go GC: Latency Problem Solved presentation or the slides.

By Richard Hudson

Myths about /dev/urandom

31 August 2015 - 4:52pm
Myths about /dev/urandom

There are a few things about /dev/urandom and /dev/random that are repeated again and again. Still they are false.

I'm mostly talking about reasonably recent Linux systems, not other UNIX-like systems.


/dev/urandom is insecure. Always use /dev/random for cryptographic purposes.

Fact: /dev/urandom is the preferred source of cryptographic randomness on UNIX-like systems.


/dev/urandom is a pseudo random number generator, a PRNG, while /dev/random is a “true” random number generator.

Fact: Both /dev/urandom and /dev/random are using the exact same CSPRNG (a cryptographically secure pseudorandom number generator). They only differ in very few ways that have nothing to do with “true” randomness.


/dev/random is unambiguously the better choice for cryptography. Even if /dev/urandom were comparably secure, there's no reason to choose the latter.

Fact: /dev/random has a very nasty problem: it blocks.


But that's good! /dev/random gives out exactly as much randomness as it has entropy in its pool. /dev/urandom will give you insecure random numbers, even though it has long run out of entropy.

Fact: No. Even disregarding issues like availability and subsequent manipulation by users, the issue of entropy “running low” is a straw man. About 256 bits of entropy are enough to get computationally secure numbers for a long, long time.

And the fun only starts here: how does /dev/random know how much entropy there is available to give out? Stay tuned!


But cryptographers always talk about constant re-seeding. Doesn't that contradict your last point?

Fact: You got me! Kind of. It is true, the random number generator is constantly re-seeded using whatever entropy the system can lay its hands on. But that has (partly) other reasons.

Look, I don't claim that injecting entropy is bad. It's good. I just claim that it's bad to block when the entropy estimate is low.


That's all good and nice, but even the man page for /dev/(u)random contradicts you! Does anyone who knows about this stuff actually agree with you?

Fact: No, it really doesn't. It seems to imply that /dev/urandom is insecure for cryptographic use, unless you really understand all that cryptographic jargon.

The man page does recommend the use of /dev/random in some cases (it doesn't hurt, in my opinion, but is not strictly necessary), but it also recommends /dev/urandom as the device to use for “normal” cryptographic use.

And while appeal to authority is usually nothing to be proud of, in cryptographic issues you're generally right to be careful and try to get the opinion of a domain expert.

And yes, quite a few experts share my view that /dev/urandom is the go-to solution for your random number needs in a cryptography context on UNIX-like systems. Obviously, their opinions influenced mine, not the other way around.

Hard to believe, right? I must certainly be wrong! Well, read on and let me try to convince you.

I tried to keep it out, but I fear there are two preliminaries to be taken care of, before we can really tackle all those points.

Namely, what is randomness, or better: what kind of randomness am I talking about here?

And, even more important, I'm really not being condescending. I have written this document to have a thing to point to, when this discussion comes up again. More than 140 characters. Without repeating myself again and again. Being able to hone the writing and the arguments itself, benefitting many discussions in many venues.

And I'm certainly willing to hear differing opinions. I'm just saying that it won't be enough to state that /dev/urandom is bad. You need to identify the points you're disagreeing with and engage them.

You're saying I'm stupid!

Emphatically no!

Actually, I used to believe that /dev/urandom was insecure myself, a few years ago. And it's something you and me almost had to believe, because all those highly respected people on Usenet, in web forums and today on Twitter told us. Even the man page seems to say so. Who were we to dismiss their convincing argument about “entropy running low”?

This misconception isn't so rampant because people are stupid, it is because with a little knowledge about cryptography (namely some vague idea what entropy is) it's very easy to be convinced of it. Intuition almost forces us there. Unfortunately intuition is often wrong in cryptography. So it is here.

True randomness

What does it mean for random numbers to be “truly random”?

I don't want to dive into that issue too deep, because it quickly gets philosophical. Discussions have been known to unravel fast, because everyone can wax about their favorite model of randomness, without paying attention to anyone else. Or even making himself understood.

I believe that the “gold standard” for “true randomness” are quantum effects. Observe a photon pass through a semi-transparent mirror. Or not. Observe some radioactive material emit alpha particles. It's the best idea we have when it comes to randomness in the world. Other people might reasonably believe that those effects aren't truly random. Or even that there is no randomness in the world at all. Let a million flowers bloom.

Cryptographers often circumvent this philosophical debate by disregarding what it means for randomness to be “true”. They care about unpredictability. As long as nobody can get any information about the next random number, we're fine. And when you're talking about random numbers as a prerequisite in using cryptography, that's what you should aim for, in my opinion.

Anyway, I don't care much about those “philosophically secure” random numbers, as I like to think of your “true” random numbers.

Two kinds of security, one that matters

But let's assume you've obtained those “true” random numbers. What are you going to do with them?

You print them out, frame them and hang them on your living-room wall, to revel in the beauty of a quantum universe? That's great, and I certainly understand.

Wait, what? You're using them? For cryptographic purposes? Well, that spoils everything, because now things get a bit ugly.

You see, your truly-random, quantum effect blessed random numbers are put into some less respectable, real-world tarnished algorithms.

Because almost all of the cryptographic algorithms we use do not hold up to information-theoretic security. They can “only” offer computational security. The two exceptions that come to my mind are Shamir's Secret Sharing and the One-time pad. And while the first one may be a valid counterpoint (if you actually intend to use it), the latter is utterly impractical.

But all those algorithms you know about, AES, RSA, Diffie-Hellman, Elliptic curves, and all those crypto packages you're using, OpenSSL, GnuTLS, Keyczar, your operating system's crypto API, these are only computationally secure.

What's the difference? While information-theoretically secure algorithms are secure, period, those other algorithms cannot guarantee security against an adversary with unlimited computational power who's trying all possibilities for keys. We still use them because it would take all the computers in the world taken together longer than the universe has existed, so far. That's the level of “insecurity” we're talking about here.

Unless some clever guy breaks the algorithm itself, using much less computational power. Even computational power achievable today. That's the big prize every cryptanalyst dreams about: breaking AES itself, breaking RSA itself and so on.

So now we're at the point where you don't trust the inner building blocks of the random number generator, insisting on “true randomness” instead of “pseudo randomness”. But then you're using those “true” random numbers in algorithms that you so despise that you didn't want them near your random number generator in the first place!

Truth is, when state-of-the-art hash algorithms are broken, or when state-of-the-art block ciphers are broken, it doesn't matter that you get “philosophically insecure” random numbers because of them. You've got nothing left to securely use them for anyway.

So just use those computationally-secure random numbers for your computationally-secure algorithms. In other words: use /dev/urandom.

Structure of Linux's random number generator An incorrect view

Chances are, your idea of the kernel's random number generator is something similar to this:

“True randomness”, albeit possibly skewed and biased, enters the system and its entropy is precisely counted and immediately added to an internal entropy counter. After de-biasing and whitening it's entering the kernel's entropy pool, where both /dev/random and /dev/urandom get their random numbers from.

The “true” random number generator, /dev/random, takes those random numbers straight out of the pool, if the entropy count is sufficient for the number of requested numbers, decreasing the entropy counter, of course. If not, it blocks until new entropy has entered the system.

The important thing in this narrative is that /dev/random basically yields the numbers that have been input by those randomness sources outside, after only the necessary whitening. Nothing more, just pure randomness.

/dev/urandom, so the story goes, is doing the same thing. Except when there isn't sufficient entropy in the system. In contrast to /dev/random, it does not block, but gets “low quality random” numbers from a pseudorandom number generator (conceded, a cryptographically secure one) that is running alongside the rest of the random number machinery. This CSPRNG is just seeded once (or maybe every now and then, it doesn't matter) with “true randomness” from the randomness pool, but you can't really trust it.

In this view, that seems to be in a lot of people's minds when they're talking about random numbers on Linux, avoiding /dev/urandom is plausible.

Because either there is enough entropy left, then you get the same you'd have gotten from /dev/random. Or there isn't, then you get those low-quality random numbers from a CSPRNG that almost never saw high-entropy input.

Devilish, right? Unfortunately, also utterly wrong. In reality, the internal structure of the random number generator looks like this.

A better simplification

This is a pretty rough simplification. In fact, there isn't just one, but three pools filled with entropy. One primary pool, and one for /dev/random and /dev/urandom each, feeding off the primary pool. Those three pools all have their own entropy counts, but the counts of the secondary pools (for /dev/random and /dev/urandom) are mostly close to zero, and “fresh” entropy flows from the primary pool when needed, decreasing its entropy count. Also there is a lot of mixing and re-injecting outputs back into the system going on. All of this is far more detail than is necessary for this document.

See the big difference? The CSPRNG is not running alongside the random number generator, filling in for those times when /dev/urandom wants to output something, but has nothing good to output. The CSPRNG is an integral part of the random number generation process. There is no /dev/random handing out “good and pure” random numbers straight from the whitener. Every randomness source's input is thoroughly mixed and hashed inside the CSPRNG, before it emerges as random numbers, either via /dev/urandom or /dev/random.

Another important difference is that there is no entropy counting going on here, but estimation. The amount of entropy some source is giving you isn't something obvious that you just get, along with the data. It has to be estimated. Please note that when your estimate is too optimistic, the dearly held property of /dev/random, that it's only giving out as many random numbers as available entropy allows, is gone. Unfortunately, it's hard to estimate the amount of entropy.

The Linux kernel uses only the arrival times of events to estimate their entropy. It does that by interpolating polynomials of those arrival times, to calculate “how surprising” the actual arrival time was, according to the model. Whether this polynomial interpolation model is the best way to estimate entropy is an interesting question. There is also the problem that internal hardware restrictions might influence those arrival times. The sampling rates of all kinds of hardware components may also play a role, because it directly influences the values and the granularity of those event arrival times.

In the end, to the best of our knowledge, the kernel's entropy estimate is pretty good. Which means it's conservative. People argue about how good it really is, but that issue is far above my head. Still, if you insist on never handing out random numbers that are not “backed” by sufficient entropy, you might be nervous here. I'm sleeping sound because I don't care about the entropy estimate.

So to make one thing crystal clear: both /dev/random and /dev/urandom are fed by the same CSPRNG. Only the behavior when their respective pool runs out of entropy, according to some estimate, differs: /dev/random blocks, while /dev/urandom does not.

What's wrong with blocking?

Have you ever waited for /dev/random to give you more random numbers? Generating a PGP key inside a virtual machine maybe? Connecting to a web server that's waiting for more random numbers to create an ephemeral session key?

That's the problem. It inherently runs counter to availability. So your system is not working. It's not doing what you built it to do. Obviously, that's bad. You wouldn't have built it if you didn't need it.

I'm working on safety-related systems in factory automation. Can you guess what the main reason for failures of safety systems is? Manipulation. Simple as that. Something about the safety measure bugged the worker. It took too much time, was too inconvenient, whatever. People are very resourceful when it comes to finding “inofficial solutions”.

But the problem runs even deeper: people don't like to be stopped in their ways. They will devise workarounds, concoct bizarre machinations to just get it running. People who don't know anything about cryptography. Normal people.

Why not patching out the call to random()? Why not having some guy in a web forum tell you how to use some strange ioctl to increase the entropy counter? Why not switch off SSL altogether?

In the end you just educate your users to do foolish things that compromise your system's security without you ever knowing about it.

It's easy to disregard availability, usability or other nice properties. Security trumps everything, right? So better be inconvenient, unavailable or unusable than feign security.

But that's a false dichotomy. Blocking is not necessary for security. As we saw, /dev/urandom gives you the same kind of random numbers as /dev/random, straight out of a CSPRNG. Use it!

The CSPRNGs are alright

But now everything sounds really bleak. If even the high-quality random numbers from /dev/random are coming out of a CSPRNG, how can we use them for high-security purposes?

It turns out, that “looking random” is the basic requirement for a lot of our cryptographic building blocks. If you take the output of a cryptographic hash, it has to be indistinguishable from a random string so that cryptographers will accept it. If you take a block cipher, its output (without knowing the key) must also be indistinguishable from random data.

If anyone could gain an advantage over brute force breaking of cryptographic building blocks, using some perceived weakness of those CSPRNGs over “true” randomness, then it's the same old story: you don't have anything left. Block ciphers, hashes, everything is based on the same mathematical fundament as CSPRNGs. So don't be afraid.

What about entropy running low?

It doesn't matter.

The underlying cryptographic building blocks are designed such that an attacker cannot predict the outcome, as long as there was enough randomness (a.k.a. entropy) in the beginning. A usual lower limit for “enough” may be 256 bits. No more.

Considering that we were pretty hand-wavey about the term “entropy” in the first place, it feels right. As we saw, the kernel's random number generator cannot even precisely know the amount of entropy entering the system. Only an estimate. And whether the model that's the basis for the estimate is good enough is pretty unclear, too.

Re-seeding

But if entropy is so unimportant, why is fresh entropy constantly being injected into the random number generator?

djb remarked that more entropy actually can hurt.

First, it cannot hurt. If you've got more randomness just lying around, by all means use it!

There is another reason why re-seeding the random number generator every now and then is important:

Imagine an attacker knows everything about your random number generator's internal state. That's the most severe security compromise you can imagine, the attacker has full access to the system.

You've totally lost now, because the attacker can compute all future outputs from this point on.

But over time, with more and more fresh entropy being mixed into it, the internal state gets more and more random again. So that such a random number generator's design is kind of self-healing.

But this is injecting entropy into the generator's internal state, it has nothing to do with blocking its output.

The random and urandom man page

The man page for /dev/random and /dev/urandom is pretty effective when it comes to instilling fear into the gullible programmer's mind:

A read from the /dev/urandom device will not block waiting for more entropy. As a result, if there is not sufficient entropy in the entropy pool, the returned values are theoretically vulnerable to a cryptographic attack on the algorithms used by the driver. Knowledge of how to do this is not available in the current unclassified literature, but it is theoretically possible that such an attack may exist. If this is a concern in your application, use /dev/random instead.

Such an attack is not known in “unclassified literature”, but the NSA certainly has one in store, right? And if you're really concerned about this (you should!), please use /dev/random, and all your problems are solved.

The truth is, while there may be such an attack available to secret services, evil hackers or the Bogeyman, it's just not rational to just take it as a given.

And even if you need that peace of mind, let me tell you a secret: no practical attacks on AES, SHA-3 or other solid ciphers and hashes are known in the “unclassified” literature, either. Are you going to stop using those, as well? Of course not!

Now the fun part: “use /dev/random instead”. While /dev/random does not block, its random number output comes from the very same CSPRNG as /dev/urandom's.

If you really need information-theoretically secure random numbers (you don't!), and that's about the only reason why the entropy of the CSPRNGs input matters, you can't use /dev/random, either!

The man page is silly, that's all. At least it tries to redeem itself with this:

If you are unsure about whether you should use /dev/random or /dev/urandom, then probably you want to use the latter. As a general rule, /dev/urandom should be used for everything except long-lived GPG/SSL/SSH keys.

Fine. I think it's unnecessary, but if you want to use /dev/random for your “long-lived keys”, by all means, do so! You'll be waiting a few seconds typing stuff on your keyboard, that's no problem.

But please don't make connections to a mail server hang forever, just because you “wanted to be safe”.

Orthodoxy

The view espoused here is certainly a tiny minority's opinions on the Internet. But ask a real cryptographer, you'll be hard pressed to find someone who sympathizes much with that blocking /dev/random.

Let's take Daniel Bernstein, better known as djb:

Cryptographers are certainly not responsible for this superstitious nonsense. Think about this for a moment: whoever wrote the /dev/random manual page seems to simultaneously believe that

  • (1) we can't figure out how to deterministically expand one 256-bit /dev/random output into an endless stream of unpredictable keys (this is what we need from urandom), but

  • (2) we _can_ figure out how to use a single key to safely encrypt many messages (this is what we need from SSL, PGP, etc.).

For a cryptographer this doesn't even pass the laugh test.

Or Thomas Pornin, who is probably one of the most helpful persons I've ever encountered on the Stackexchange sites:

The short answer is yes. The long answer is also yes. /dev/urandom yields data which is indistinguishable from true randomness, given existing technology. Getting "better" randomness than what /dev/urandom provides is meaningless, unless you are using one of the few "information theoretic" cryptographic algorithm, which is not your case (you would know it).

The man page for urandom is somewhat misleading, arguably downright wrong, when it suggests that /dev/urandom may "run out of entropy" and /dev/random should be preferred;

Or maybe Thomas Ptacek, who is not a real cryptographer in the sense of designing cryptographic algorithms or building cryptographic systems, but still the founder of a well-reputed security consultancy that's doing a lot of penetration testing and breaking bad cryptography:

Use urandom. Use urandom. Use urandom. Use urandom. Use urandom. Use urandom.

Not everything is perfect

/dev/urandom isn't perfect. The problems are twofold:

On Linux, unlike FreeBSD, /dev/urandom never blocks. Remember that the whole security rested on some starting randomness, a seed?

Linux's /dev/urandom happily gives you not-so-random numbers before the kernel even had the chance to gather entropy. When is that? At system start, booting the computer.

FreeBSD does the right thing: they don't have the distinction between /dev/random and /dev/urandom, both are the same device. At startup /dev/random blocks once until enough starting entropy has been gathered. Then it won't block ever again.

In the meantime, Linux has implemented a new syscall, originally introduced by OpenBSD as getentropy(2): getrandom(2). This syscall does the right thing: blocking until it has gathered enough initial entropy, and never blocking after that point. Of course, it is a syscall, not a character device, so it isn't as easily accessible from shell or script languages.

On Linux it isn't too bad, because Linux distributions save some random numbers when booting up the system (but after they have gathered some entropy, since the startup script doesn't run immediately after switching on the machine) into a seed file that is read next time the machine is booting. So you carry over the randomness from the last running of the machine.

Obviously that isn't as good as if you let the shutdown scripts write out the seed, because in that case there would have been much more time to gather entropy. The advantage is obviously that this does not depend on a proper shutdown with execution of the shutdown scripts (in case the computer crashes, for example).

And it doesn't help you the very first time a machine is running, but the Linux distributions usually do the same saving into a seed file when running the installer. So that's mostly okay.

Virtual machines are the other problem. Because people like to clone them, or rewind them to a previously saved check point, this seed file doesn't help you.

But the solution still isn't using /dev/random everywhere, but properly seeding each and every virtual machine after cloning, restoring a checkpoint, whatever.

tldr;

Just use /dev/urandom!

Original publication on March 16th, 2014, last changed on April 11th, 2015

Start

Myths about /dev/urandom

There are a few things about /dev/urandom and /dev/random that are repeated again and again. Still they are false.

I'm mostly talking about reasonably recent Linux systems, not other UNIX-like systems.


/dev/urandom is insecure. Always use /dev/random for cryptographic purposes.

Fact: /dev/urandom is the preferred source of cryptographic randomness on UNIX-like systems.


/dev/urandom is a pseudo random number generator, a PRNG, while /dev/random is a “true” random number generator.

Fact: Both /dev/urandom and /dev/random are using the exact same CSPRNG (a cryptographically secure pseudorandom number generator). They only differ in very few ways that have nothing to do with “true” randomness.


/dev/random is unambiguously the better choice for cryptography. Even if /dev/urandom were comparably secure, there's no reason to choose the latter.

Fact: /dev/random has a very nasty problem: it blocks.


But that's good! /dev/random gives out exactly as much randomness as it has entropy in its pool. /dev/urandom will give you insecure random numbers, even though it has long run out of entropy.

Fact: No. Even disregarding issues like availability and subsequent manipulation by users, the issue of entropy “running low” is a straw man. About 256 bits of entropy are enough to get computationally secure numbers for a long, long time.

And the fun only starts here: how does /dev/random know how much entropy there is available to give out? Stay tuned!


But cryptographers always talk about constant re-seeding. Doesn't that contradict your last point?

Fact: You got me! Kind of. It is true, the random number generator is constantly re-seeded using whatever entropy the system can lay its hands on. But that has (partly) other reasons.

Look, I don't claim that injecting entropy is bad. It's good. I just claim that it's bad to block when the entropy estimate is low.


That's all good and nice, but even the man page for /dev/(u)random contradicts you! Does anyone who knows about this stuff actually agree with you?

Fact: No, it really doesn't. It seems to imply that /dev/urandom is insecure for cryptographic use, unless you really understand all that cryptographic jargon.

The man page does recommend the use of /dev/random in some cases (it doesn't hurt, in my opinion, but is not strictly necessary), but it also recommends /dev/urandom as the device to use for “normal” cryptographic use.

And while appeal to authority is usually nothing to be proud of, in cryptographic issues you're generally right to be careful and try to get the opinion of a domain expert.

And yes, quite a few experts share my view that /dev/urandom is the go-to solution for your random number needs in a cryptography context on UNIX-like systems. Obviously, their opinions influenced mine, not the other way around.

Hard to believe, right? I must certainly be wrong! Well, read on and let me try to convince you.

I tried to keep it out, but I fear there are two preliminaries to be taken care of, before we can really tackle all those points.

Namely, what is randomness, or better: what kind of randomness am I talking about here?

And, even more important, I'm really not being condescending. I have written this document to have a thing to point to, when this discussion comes up again. More than 140 characters. Without repeating myself again and again. Being able to hone the writing and the arguments itself, benefitting many discussions in many venues.

And I'm certainly willing to hear differing opinions. I'm just saying that it won't be enough to state that /dev/urandom is bad. You need to identify the points you're disagreeing with and engage them.

You're saying I'm stupid!

Emphatically no!

Actually, I used to believe that /dev/urandom was insecure myself, a few years ago. And it's something you and me almost had to believe, because all those highly respected people on Usenet, in web forums and today on Twitter told us. Even the man page seems to say so. Who were we to dismiss their convincing argument about “entropy running low”?

This misconception isn't so rampant because people are stupid, it is because with a little knowledge about cryptography (namely some vague idea what entropy is) it's very easy to be convinced of it. Intuition almost forces us there. Unfortunately intuition is often wrong in cryptography. So it is here.

True randomness

What does it mean for random numbers to be “truly random”?

I don't want to dive into that issue too deep, because it quickly gets philosophical. Discussions have been known to unravel fast, because everyone can wax about their favorite model of randomness, without paying attention to anyone else. Or even making himself understood.

I believe that the “gold standard” for “true randomness” are quantum effects. Observe a photon pass through a semi-transparent mirror. Or not. Observe some radioactive material emit alpha particles. It's the best idea we have when it comes to randomness in the world. Other people might reasonably believe that those effects aren't truly random. Or even that there is no randomness in the world at all. Let a million flowers bloom.

Cryptographers often circumvent this philosophical debate by disregarding what it means for randomness to be “true”. They care about unpredictability. As long as nobody can get any information about the next random number, we're fine. And when you're talking about random numbers as a prerequisite in using cryptography, that's what you should aim for, in my opinion.

Anyway, I don't care much about those “philosophically secure” random numbers, as I like to think of your “true” random numbers.

Two kinds of security, one that matters

But let's assume you've obtained those “true” random numbers. What are you going to do with them?

You print them out, frame them and hang them on your living-room wall, to revel in the beauty of a quantum universe? That's great, and I certainly understand.

Wait, what? You're using them? For cryptographic purposes? Well, that spoils everything, because now things get a bit ugly.

You see, your truly-random, quantum effect blessed random numbers are put into some less respectable, real-world tarnished algorithms.

Because almost all of the cryptographic algorithms we use do not hold up to information-theoretic security. They can “only” offer computational security. The two exceptions that come to my mind are Shamir's Secret Sharing and the One-time pad. And while the first one may be a valid counterpoint (if you actually intend to use it), the latter is utterly impractical.

But all those algorithms you know about, AES, RSA, Diffie-Hellman, Elliptic curves, and all those crypto packages you're using, OpenSSL, GnuTLS, Keyczar, your operating system's crypto API, these are only computationally secure.

What's the difference? While information-theoretically secure algorithms are secure, period, those other algorithms cannot guarantee security against an adversary with unlimited computational power who's trying all possibilities for keys. We still use them because it would take all the computers in the world taken together longer than the universe has existed, so far. That's the level of “insecurity” we're talking about here.

Unless some clever guy breaks the algorithm itself, using much less computational power. Even computational power achievable today. That's the big prize every cryptanalyst dreams about: breaking AES itself, breaking RSA itself and so on.

So now we're at the point where you don't trust the inner building blocks of the random number generator, insisting on “true randomness” instead of “pseudo randomness”. But then you're using those “true” random numbers in algorithms that you so despise that you didn't want them near your random number generator in the first place!

Truth is, when state-of-the-art hash algorithms are broken, or when state-of-the-art block ciphers are broken, it doesn't matter that you get “philosophically insecure” random numbers because of them. You've got nothing left to securely use them for anyway.

So just use those computationally-secure random numbers for your computationally-secure algorithms. In other words: use /dev/urandom.

Structure of Linux's random number generator An incorrect view

Chances are, your idea of the kernel's random number generator is something similar to this:

“True randomness”, albeit possibly skewed and biased, enters the system and its entropy is precisely counted and immediately added to an internal entropy counter. After de-biasing and whitening it's entering the kernel's entropy pool, where both /dev/random and /dev/urandom get their random numbers from.

The “true” random number generator, /dev/random, takes those random numbers straight out of the pool, if the entropy count is sufficient for the number of requested numbers, decreasing the entropy counter, of course. If not, it blocks until new entropy has entered the system.

The important thing in this narrative is that /dev/random basically yields the numbers that have been input by those randomness sources outside, after only the necessary whitening. Nothing more, just pure randomness.

/dev/urandom, so the story goes, is doing the same thing. Except when there isn't sufficient entropy in the system. In contrast to /dev/random, it does not block, but gets “low quality random” numbers from a pseudorandom number generator (conceded, a cryptographically secure one) that is running alongside the rest of the random number machinery. This CSPRNG is just seeded once (or maybe every now and then, it doesn't matter) with “true randomness” from the randomness pool, but you can't really trust it.

In this view, that seems to be in a lot of people's minds when they're talking about random numbers on Linux, avoiding /dev/urandom is plausible.

Because either there is enough entropy left, then you get the same you'd have gotten from /dev/random. Or there isn't, then you get those low-quality random numbers from a CSPRNG that almost never saw high-entropy input.

Devilish, right? Unfortunately, also utterly wrong. In reality, the internal structure of the random number generator looks like this.

A better simplification

This is a pretty rough simplification. In fact, there isn't just one, but three pools filled with entropy. One primary pool, and one for /dev/random and /dev/urandom each, feeding off the primary pool. Those three pools all have their own entropy counts, but the counts of the secondary pools (for /dev/random and /dev/urandom) are mostly close to zero, and “fresh” entropy flows from the primary pool when needed, decreasing its entropy count. Also there is a lot of mixing and re-injecting outputs back into the system going on. All of this is far more detail than is necessary for this document.

See the big difference? The CSPRNG is not running alongside the random number generator, filling in for those times when /dev/urandom wants to output something, but has nothing good to output. The CSPRNG is an integral part of the random number generation process. There is no /dev/random handing out “good and pure” random numbers straight from the whitener. Every randomness source's input is thoroughly mixed and hashed inside the CSPRNG, before it emerges as random numbers, either via /dev/urandom or /dev/random.

Another important difference is that there is no entropy counting going on here, but estimation. The amount of entropy some source is giving you isn't something obvious that you just get, along with the data. It has to be estimated. Please note that when your estimate is too optimistic, the dearly held property of /dev/random, that it's only giving out as many random numbers as available entropy allows, is gone. Unfortunately, it's hard to estimate the amount of entropy.

The Linux kernel uses only the arrival times of events to estimate their entropy. It does that by interpolating polynomials of those arrival times, to calculate “how surprising” the actual arrival time was, according to the model. Whether this polynomial interpolation model is the best way to estimate entropy is an interesting question. There is also the problem that internal hardware restrictions might influence those arrival times. The sampling rates of all kinds of hardware components may also play a role, because it directly influences the values and the granularity of those event arrival times.

In the end, to the best of our knowledge, the kernel's entropy estimate is pretty good. Which means it's conservative. People argue about how good it really is, but that issue is far above my head. Still, if you insist on never handing out random numbers that are not “backed” by sufficient entropy, you might be nervous here. I'm sleeping sound because I don't care about the entropy estimate.

So to make one thing crystal clear: both /dev/random and /dev/urandom are fed by the same CSPRNG. Only the behavior when their respective pool runs out of entropy, according to some estimate, differs: /dev/random blocks, while /dev/urandom does not.

What's wrong with blocking?

Have you ever waited for /dev/random to give you more random numbers? Generating a PGP key inside a virtual machine maybe? Connecting to a web server that's waiting for more random numbers to create an ephemeral session key?

That's the problem. It inherently runs counter to availability. So your system is not working. It's not doing what you built it to do. Obviously, that's bad. You wouldn't have built it if you didn't need it.

I'm working on safety-related systems in factory automation. Can you guess what the main reason for failures of safety systems is? Manipulation. Simple as that. Something about the safety measure bugged the worker. It took too much time, was too inconvenient, whatever. People are very resourceful when it comes to finding “inofficial solutions”.

But the problem runs even deeper: people don't like to be stopped in their ways. They will devise workarounds, concoct bizarre machinations to just get it running. People who don't know anything about cryptography. Normal people.

Why not patching out the call to random()? Why not having some guy in a web forum tell you how to use some strange ioctl to increase the entropy counter? Why not switch off SSL altogether?

In the end you just educate your users to do foolish things that compromise your system's security without you ever knowing about it.

It's easy to disregard availability, usability or other nice properties. Security trumps everything, right? So better be inconvenient, unavailable or unusable than feign security.

But that's a false dichotomy. Blocking is not necessary for security. As we saw, /dev/urandom gives you the same kind of random numbers as /dev/random, straight out of a CSPRNG. Use it!

The CSPRNGs are alright

But now everything sounds really bleak. If even the high-quality random numbers from /dev/random are coming out of a CSPRNG, how can we use them for high-security purposes?

It turns out, that “looking random” is the basic requirement for a lot of our cryptographic building blocks. If you take the output of a cryptographic hash, it has to be indistinguishable from a random string so that cryptographers will accept it. If you take a block cipher, its output (without knowing the key) must also be indistinguishable from random data.

If anyone could gain an advantage over brute force breaking of cryptographic building blocks, using some perceived weakness of those CSPRNGs over “true” randomness, then it's the same old story: you don't have anything left. Block ciphers, hashes, everything is based on the same mathematical fundament as CSPRNGs. So don't be afraid.

What about entropy running low?

It doesn't matter.

The underlying cryptographic building blocks are designed such that an attacker cannot predict the outcome, as long as there was enough randomness (a.k.a. entropy) in the beginning. A usual lower limit for “enough” may be 256 bits. No more.

Considering that we were pretty hand-wavey about the term “entropy” in the first place, it feels right. As we saw, the kernel's random number generator cannot even precisely know the amount of entropy entering the system. Only an estimate. And whether the model that's the basis for the estimate is good enough is pretty unclear, too.

Re-seeding

But if entropy is so unimportant, why is fresh entropy constantly being injected into the random number generator?

djb remarked that more entropy actually can hurt.

First, it cannot hurt. If you've got more randomness just lying around, by all means use it!

There is another reason why re-seeding the random number generator every now and then is important:

Imagine an attacker knows everything about your random number generator's internal state. That's the most severe security compromise you can imagine, the attacker has full access to the system.

You've totally lost now, because the attacker can compute all future outputs from this point on.

But over time, with more and more fresh entropy being mixed into it, the internal state gets more and more random again. So that such a random number generator's design is kind of self-healing.

But this is injecting entropy into the generator's internal state, it has nothing to do with blocking its output.

The random and urandom man page

The man page for /dev/random and /dev/urandom is pretty effective when it comes to instilling fear into the gullible programmer's mind:

A read from the /dev/urandom device will not block waiting for more entropy. As a result, if there is not sufficient entropy in the entropy pool, the returned values are theoretically vulnerable to a cryptographic attack on the algorithms used by the driver. Knowledge of how to do this is not available in the current unclassified literature, but it is theoretically possible that such an attack may exist. If this is a concern in your application, use /dev/random instead.

Such an attack is not known in “unclassified literature”, but the NSA certainly has one in store, right? And if you're really concerned about this (you should!), please use /dev/random, and all your problems are solved.

The truth is, while there may be such an attack available to secret services, evil hackers or the Bogeyman, it's just not rational to just take it as a given.

And even if you need that peace of mind, let me tell you a secret: no practical attacks on AES, SHA-3 or other solid ciphers and hashes are known in the “unclassified” literature, either. Are you going to stop using those, as well? Of course not!

Now the fun part: “use /dev/random instead”. While /dev/random does not block, its random number output comes from the very same CSPRNG as /dev/urandom's.

If you really need information-theoretically secure random numbers (you don't!), and that's about the only reason why the entropy of the CSPRNGs input matters, you can't use /dev/random, either!

The man page is silly, that's all. At least it tries to redeem itself with this:

If you are unsure about whether you should use /dev/random or /dev/urandom, then probably you want to use the latter. As a general rule, /dev/urandom should be used for everything except long-lived GPG/SSL/SSH keys.

Fine. I think it's unnecessary, but if you want to use /dev/random for your “long-lived keys”, by all means, do so! You'll be waiting a few seconds typing stuff on your keyboard, that's no problem.

But please don't make connections to a mail server hang forever, just because you “wanted to be safe”.

Orthodoxy

The view espoused here is certainly a tiny minority's opinions on the Internet. But ask a real cryptographer, you'll be hard pressed to find someone who sympathizes much with that blocking /dev/random.

Let's take Daniel Bernstein, better known as djb:

Cryptographers are certainly not responsible for this superstitious nonsense. Think about this for a moment: whoever wrote the /dev/random manual page seems to simultaneously believe that

  • (1) we can't figure out how to deterministically expand one 256-bit /dev/random output into an endless stream of unpredictable keys (this is what we need from urandom), but

  • (2) we _can_ figure out how to use a single key to safely encrypt many messages (this is what we need from SSL, PGP, etc.).

For a cryptographer this doesn't even pass the laugh test.

Or Thomas Pornin, who is probably one of the most helpful persons I've ever encountered on the Stackexchange sites:

The short answer is yes. The long answer is also yes. /dev/urandom yields data which is indistinguishable from true randomness, given existing technology. Getting "better" randomness than what /dev/urandom provides is meaningless, unless you are using one of the few "information theoretic" cryptographic algorithm, which is not your case (you would know it).

The man page for urandom is somewhat misleading, arguably downright wrong, when it suggests that /dev/urandom may "run out of entropy" and /dev/random should be preferred;

Or maybe Thomas Ptacek, who is not a real cryptographer in the sense of designing cryptographic algorithms or building cryptographic systems, but still the founder of a well-reputed security consultancy that's doing a lot of penetration testing and breaking bad cryptography:

Use urandom. Use urandom. Use urandom. Use urandom. Use urandom. Use urandom.

Not everything is perfect

/dev/urandom isn't perfect. The problems are twofold:

On Linux, unlike FreeBSD, /dev/urandom never blocks. Remember that the whole security rested on some starting randomness, a seed?

Linux's /dev/urandom happily gives you not-so-random numbers before the kernel even had the chance to gather entropy. When is that? At system start, booting the computer.

FreeBSD does the right thing: they don't have the distinction between /dev/random and /dev/urandom, both are the same device. At startup /dev/random blocks once until enough starting entropy has been gathered. Then it won't block ever again.

In the meantime, Linux has implemented a new syscall, originally introduced by OpenBSD as getentropy(2): getrandom(2). This syscall does the right thing: blocking until it has gathered enough initial entropy, and never blocking after that point. Of course, it is a syscall, not a character device, so it isn't as easily accessible from shell or script languages.

On Linux it isn't too bad, because Linux distributions save some random numbers when booting up the system (but after they have gathered some entropy, since the startup script doesn't run immediately after switching on the machine) into a seed file that is read next time the machine is booting. So you carry over the randomness from the last running of the machine.

Obviously that isn't as good as if you let the shutdown scripts write out the seed, because in that case there would have been much more time to gather entropy. The advantage is obviously that this does not depend on a proper shutdown with execution of the shutdown scripts (in case the computer crashes, for example).

And it doesn't help you the very first time a machine is running, but the Linux distributions usually do the same saving into a seed file when running the installer. So that's mostly okay.

Virtual machines are the other problem. Because people like to clone them, or rewind them to a previously saved check point, this seed file doesn't help you.

But the solution still isn't using /dev/random everywhere, but properly seeding each and every virtual machine after cloning, restoring a checkpoint, whatever.

tldr;

Just use /dev/urandom!

Original publication on March 16th, 2014, last changed on April 11th, 2015

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Google Votes: A Liquid Democracy Experiment on a Corporate Social Network

31 August 2015 - 3:05pm

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A native hypervisor is coming to OpenBSD

31 August 2015 - 2:11pm
'virtualization support' - MARC [prev in list] [next in list] [prev in thread] [next in thread] List: openbsd-tech Subject: virtualization support From: Mike Larkin <mlarkin () azathoth ! net> Date: 2015-08-31 17:58:23 Message-ID: 20150831175823.GB1265 () azathoth ! net [Download message RAW] TL;DR - a native hypervisor is coming. stay tuned. For the last few months, I've been working on a hypervisor for OpenBSD. The idea for this started a few years ago, and after playing around with it from time to time, things really started to take shape around the time of the Brisbane hackathon earlier this year. As development accelerated, the OpenBSD Foundation generously offered to fund the project so that I could focus on it in more earnest. At this point, I think I've made sufficient progress that a public announcement is in order. I've also reached the point where I think other developers can step in and help out as much of the gooey bits in the core of the vmm are functioning the way I want. Presently, the vmm code I've built is capable of launching a kernel and asking for the root filesystem; it doesn't do much more than that for now. However, getting to this point invovled building most of the scaffolding needed to finish the rest, and like I stated before, more people can now more easily help with what's left (basically the virtio(4) emulation for disks and network interfaces). One might ask - why not port one of the other hypervisors out there instead of rolling your own from scratch? Fair question. However, for various technical reasons, choosing to port an existing vmm just didn't make a whole lot of sense. For example, I've been baking in support for things that the other implementations don't care about (namely i386 support, shadow paging, nested virtualization, support for legacy peripherals, etc) and trying to backfit support for those things into another hypervisor would probably have been just as hard as building it from the ground up. The inevitable questions: Q. What OSes can I run? A. To start, OSes that support virtio-based devices (most of the CPU goo is done and is basically the same across most OSes once you get that part finished). Later, we'll see if we can expose a place for qemu to attach (maybe mimic KVM) to run legacy OSes or OSes that require BIOS/UEFI boot support. There is no legacy-free mandate in this vmm. Q. When will it be ready? A. Hard to say. I hope by the end of October, but no promises. A lot also depends on how much help I get writing some of the virtio backends. Q. What will be the CPU requirements? A. Any AMD or Intel CPU that supports hardware virtualization (SVM for AMD, and VMX for Intel). For those CPUs that don't support RVI or EPT, we'll use shadow paging. Q. What will be the OS requirements? A. The core tools (vmd(8) and vmmctl(8)) and the main vmm (vmm(4)) will be built in to base, on i386 and amd64. This should be sufficient to run virtio based guests without any additional software requirements. Q. Yuck, i386? A. Yes. It helps find bugs. And I urge you to review my last dozen or so commits to i386 for another reason. And now, the most important question: Q. How can I help? A. I would have likely had no time to work on this project for the past few months had it not been for the generous sponsorship of the OpenBSD Foundation. Your donations made that possible, and other projects like this. So, you can help by donating. If you think a hypervisor in OpenBSD is something you'd like to take advantage of, I urge you to go make a donation right now. http://www.openbsdfoundation.org/donations.html --- And finally, a sample boot: Enable vmm mode (ala apm/apmd): # vmmctl -e cpu0: entered VMM mode Start a VM: # vmmctl -S -c openbsd_amd64.vmrc /dev/ttyp0 Attach to VM console: # cu -l /dev/ttyp0 exit save va/pa 0xfffff000bcff000 0xbcff000 exit load va/pa 0xfffff000bd1e000 0xbd1e000 entry load va/pa 0xffffff000bd2c000 0xbd2c000 vmd: new vm with id 1 created loading 64 bit kernel warning: bcopy during ELF kernel load not supported warning: bcopy during ELF kernel load not supported mark[start] = 0x1000000 mark[entry] = 0x1000160 mark[nsym] = 0x1 mark[sym] = 0x1939000 mark[end] = 0x1a1de00 mark[random] = 0x18a4000 mark[erandom] = 0x18a6408 vmd: all vcpu run threads for vm 3 launched vcpu_run_vmx: yielding the cpu vmd: waiting on thread 0 vcpu_run_vmx: yielding the cpu vcpu_run_vmx: yielding the cpu loading 0x1a44000-0x4000000 (0x1a44-0x4000) loading 0x100000-0x1000000 avail_start = 0x26000 avail_end = 0x4000000 First_avail = 0x1a44000 [ bsd ELF symbol table not valid: bad magic ] [ no symbol table formats found ] Copyright (c) 1982, 1986, 1989, 1991, 1993 The Regents of the University of California. All rights reserved. Copyright (c) 1995-2015 OpenBSD. All rights reserved. http://www.OpenBSD.org OpenBSD 5.8-current (GENERIC) #204: Mon Aug 31 01:13:40 PDT 2015 mlarkin@miskatonic.azathoth.net:/export/bin/src/OpenBSD/vmm/src/sys/arch/amd64/compile/GENERIC vmd: i8253 PIT: 16 bit counter I/O not supported RTC BIOS diagnostic error ff<clo ck_battery,ROM_cksum,config_unit,memory_size,fixed_disk,invalid_time> real mem = 50331648 (48MB) avail mem = 45101056 (43MB) mpath0 at root scsibus0 at mpath0: 256 targets mainbus0 at root bios0 at mainbus0 acpi at bios0 not configured cpu0 at mainbus0: (uniprocessor) cpu0: Intel(R) Core(TM) i7-3770K CPU @ 3.50GHz cpu0: FPU,VME,DE,PSE,MSR,PAE,MCE,CX8,APIC,SEP,MTRR,PGE,MCA,CMOV,PAT,PSE36,CFLUSH ,DS,MMX,FXSR,SSE,SSE2,SS,HTT,PBE,SSE3,PCLMUL,DTES64,DS-CPL,SSSE3,CX16,xTPR,PCID, SSE4.1,SSE4.2,x2APIC,POPCNT,DEADLINE,AES,AVX,F16C,RDRAND,HV,ITSC,FSGSBASE,SMEP,E RMS pvbus0 at mainbus0: OpenBSD vmx_handle_cpuid: unsupported rax=0x40000100 pci0 at mainbus0 bus 0 isa0 at mainbus0 isadma0 at isa0 com0 at isa0 port 0x3f8/8 irq 4: ns8250, no fifo com0: console vmm at mainbus0 not configured vmx_handle_cr: mov to cr8 @ ffffffff8131854a nvram: invalid checksum vscsi0 at root scsibus1 at vscsi0: 256 targets softraid0 at root scsibus2 at softraid0: 256 targets root device: [prev in list] [next in list] [prev in thread] [next in thread] Configure | About | News | Add a list | Sponsored by KoreLogic 'virtualization support' - MARC [prev in list] [next in list] [prev in thread] [next in thread] List: openbsd-tech Subject: virtualization support From: Mike Larkin <mlarkin () azathoth ! net> Date: 2015-08-31 17:58:23 Message-ID: 20150831175823.GB1265 () azathoth ! net [Download message RAW] TL;DR - a native hypervisor is coming. stay tuned. For the last few months, I've been working on a hypervisor for OpenBSD. The idea for this started a few years ago, and after playing around with it from time to time, things really started to take shape around the time of the Brisbane hackathon earlier this year. As development accelerated, the OpenBSD Foundation generously offered to fund the project so that I could focus on it in more earnest. At this point, I think I've made sufficient progress that a public announcement is in order. I've also reached the point where I think other developers can step in and help out as much of the gooey bits in the core of the vmm are functioning the way I want. Presently, the vmm code I've built is capable of launching a kernel and asking for the root filesystem; it doesn't do much more than that for now. However, getting to this point invovled building most of the scaffolding needed to finish the rest, and like I stated before, more people can now more easily help with what's left (basically the virtio(4) emulation for disks and network interfaces). One might ask - why not port one of the other hypervisors out there instead of rolling your own from scratch? Fair question. However, for various technical reasons, choosing to port an existing vmm just didn't make a whole lot of sense. For example, I've been baking in support for things that the other implementations don't care about (namely i386 support, shadow paging, nested virtualization, support for legacy peripherals, etc) and trying to backfit support for those things into another hypervisor would probably have been just as hard as building it from the ground up. The inevitable questions: Q. What OSes can I run? A. To start, OSes that support virtio-based devices (most of the CPU goo is done and is basically the same across most OSes once you get that part finished). Later, we'll see if we can expose a place for qemu to attach (maybe mimic KVM) to run legacy OSes or OSes that require BIOS/UEFI boot support. There is no legacy-free mandate in this vmm. Q. When will it be ready? A. Hard to say. I hope by the end of October, but no promises. A lot also depends on how much help I get writing some of the virtio backends. Q. What will be the CPU requirements? A. Any AMD or Intel CPU that supports hardware virtualization (SVM for AMD, and VMX for Intel). For those CPUs that don't support RVI or EPT, we'll use shadow paging. Q. What will be the OS requirements? A. The core tools (vmd(8) and vmmctl(8)) and the main vmm (vmm(4)) will be built in to base, on i386 and amd64. This should be sufficient to run virtio based guests without any additional software requirements. Q. Yuck, i386? A. Yes. It helps find bugs. And I urge you to review my last dozen or so commits to i386 for another reason. And now, the most important question: Q. How can I help? A. I would have likely had no time to work on this project for the past few months had it not been for the generous sponsorship of the OpenBSD Foundation. Your donations made that possible, and other projects like this. So, you can help by donating. If you think a hypervisor in OpenBSD is something you'd like to take advantage of, I urge you to go make a donation right now. http://www.openbsdfoundation.org/donations.html --- And finally, a sample boot: Enable vmm mode (ala apm/apmd): # vmmctl -e cpu0: entered VMM mode Start a VM: # vmmctl -S -c openbsd_amd64.vmrc /dev/ttyp0 Attach to VM console: # cu -l /dev/ttyp0 exit save va/pa 0xfffff000bcff000 0xbcff000 exit load va/pa 0xfffff000bd1e000 0xbd1e000 entry load va/pa 0xffffff000bd2c000 0xbd2c000 vmd: new vm with id 1 created loading 64 bit kernel warning: bcopy during ELF kernel load not supported warning: bcopy during ELF kernel load not supported mark[start] = 0x1000000 mark[entry] = 0x1000160 mark[nsym] = 0x1 mark[sym] = 0x1939000 mark[end] = 0x1a1de00 mark[random] = 0x18a4000 mark[erandom] = 0x18a6408 vmd: all vcpu run threads for vm 3 launched vcpu_run_vmx: yielding the cpu vmd: waiting on thread 0 vcpu_run_vmx: yielding the cpu vcpu_run_vmx: yielding the cpu loading 0x1a44000-0x4000000 (0x1a44-0x4000) loading 0x100000-0x1000000 avail_start = 0x26000 avail_end = 0x4000000 First_avail = 0x1a44000 [ bsd ELF symbol table not valid: bad magic ] [ no symbol table formats found ] Copyright (c) 1982, 1986, 1989, 1991, 1993 The Regents of the University of California. All rights reserved. Copyright (c) 1995-2015 OpenBSD. All rights reserved. http://www.OpenBSD.org OpenBSD 5.8-current (GENERIC) #204: Mon Aug 31 01:13:40 PDT 2015 mlarkin@miskatonic.azathoth.net:/export/bin/src/OpenBSD/vmm/src/sys/arch/amd64/compile/GENERIC vmd: i8253 PIT: 16 bit counter I/O not supported RTC BIOS diagnostic error ff<clo ck_battery,ROM_cksum,config_unit,memory_size,fixed_disk,invalid_time> real mem = 50331648 (48MB) avail mem = 45101056 (43MB) mpath0 at root scsibus0 at mpath0: 256 targets mainbus0 at root bios0 at mainbus0 acpi at bios0 not configured cpu0 at mainbus0: (uniprocessor) cpu0: Intel(R) Core(TM) i7-3770K CPU @ 3.50GHz cpu0: FPU,VME,DE,PSE,MSR,PAE,MCE,CX8,APIC,SEP,MTRR,PGE,MCA,CMOV,PAT,PSE36,CFLUSH ,DS,MMX,FXSR,SSE,SSE2,SS,HTT,PBE,SSE3,PCLMUL,DTES64,DS-CPL,SSSE3,CX16,xTPR,PCID, SSE4.1,SSE4.2,x2APIC,POPCNT,DEADLINE,AES,AVX,F16C,RDRAND,HV,ITSC,FSGSBASE,SMEP,E RMS pvbus0 at mainbus0: OpenBSD vmx_handle_cpuid: unsupported rax=0x40000100 pci0 at mainbus0 bus 0 isa0 at mainbus0 isadma0 at isa0 com0 at isa0 port 0x3f8/8 irq 4: ns8250, no fifo com0: console vmm at mainbus0 not configured vmx_handle_cr: mov to cr8 @ ffffffff8131854a nvram: invalid checksum vscsi0 at root scsibus1 at vscsi0: 256 targets softraid0 at root scsibus2 at softraid0: 256 targets root device: [prev in list] [next in list] [prev in thread] [next in thread] Configure | About | News | Add a list | Sponsored by KoreLogic

React, Flux, RethinkDB and SageMathCloud – Summer 2015 Update

31 August 2015 - 11:57am
I've been using databases and doing web development for over 20 years, and I've never really loved any database before and definitely didn't love any web development frameworks either. That all changed for me this summer...
SageMathCloud SageMathCloud is a web application in which you collaboratively use Python, LaTeX, Markdown, Sage worksheets (sophisticated mathematics), task lists, R, Jupyter Notebooks, manage courses, write C programs, make chatrooms, and more. It is hosted on Google Compute Engine, but is also entirely open source and there is a pre-made Virtual Machine that you can download. A project in SMC is a Linux account, with resources constrained using cgroups and quotas. Many SMC users can collaborate on the same project, and have equal privileges in that project. Interaction with all file types (including Jupyter notebooks, task lists and course managements) is synchronized in realtime, like Google docs. There is also a global notifications feed that shows all editing activity on all files in all projects on which the user collaborates, which is a sort of highly technical version of Facebook's feed.
Rewrite motivation I originally wrote the SageMathCloud frontend using progressive-refinement jQuery (no third-party framework beyond that) and the Cassandra database. These were reasonable choices when I started. There are much better approaches now, which are critical to dramatically improving the user experience with SMC, and also growing the developer base. So far SMC has had no nontrivial outside contributions, probably due to the difficulty of understanding the code. In fact, I think nobody besides me has ever even installed SMC, despite these install notes.

We (me, Jon Lee, Nicholas Ruhland) are currently completely rewriting the entire frontend of SMC using React.js, Flux, and RethinkDB. We started this rewrite in June 2015, with Jon being supported by Google Summer of Code (2015), Nich being supported some by NSF grants from Randy Leveque and Rekha Thomas, and with me being unemployed.

Terrible funding situation I'm living on credit cards -- I have no NSF grant support anymore, and SageMathCloud is still losing a lot of money every month, and I'm unhappy about this situation. It was either completely quit working on SMC and instead teach or consult a lot, or lose tens of thousands of dollars. I am doing the latter right now. I was very caught off guard, since this is my first summer ever to not have NSF support since I got my Ph.D. in 2000, and I didn't expect to have my grant proposals all denied (which happened in June). There is some modest Angel investment in SageMath, Inc., but I can't bring myself to burn through that money on salary, since it would run out quickly, and I don't want to have to shut down the site due to not being able to pay the hosting bill. I've failed to get any significant free hosting, due to already getting free hosting in the past, and SageMath, Inc. not being in any incubators. For example, we tried very hard to get hosting from Google, but they flatly refused for these two reasons (they gave $60K in hosting to UW/Sage project in 2012). I'm clearly having trouble transitioning from an academic to an industry funding model. But if there are enough paying customers by January 2016, things will turn around.

Jon, Nich, and I have been working on this rewrite for three months, and hope to finish it by the end of September, when Jon and Nich will become busy with classes again. However, it seems unlikely we'll be able to finish at the current rate. Fortunately, I don't start teaching fulltime again until January, and we put a lot of work into doing a release in mid-August that fully uses RethinkDB and partly uses React.js, so that we can finish the second stage of the rewrite iteratively, without any major technical surprises.

RethinkDB Cassandra is an excellent database for many applications, but it is not the right database for SMC and I'm making no further use of Cassandra. SMC is a realtime application that does a lot more reading than writing to the database, and SMC greatly benefits from realtime push updates from the database. I've tried quite hard in the past to build an appropriate architecture for SMC on top of Cassandra, but it is the wrong tool for the job. RethinkDB scales up linearly (with sharding and replication), and has high availability and automatic failover as of version 2.1.2. See https://github.com/rethinkdb/rethinkdb/issues/4678 for my painful path to ensuring RethinkDB actually works for me (the RethinkDB developers are incredibly helpful!).
React.js I learned about React.js first from some "random podcast", then got more interested in it when Chris Swenson gave a demo at a Sage Days workshop in San Diego in May 2015. React (+Flux) is a web development framework that actually has solid ideas behind it, backed by an implementation that has been optimized and tested by a highly nontrivial real world application: namely the Facebook website. Even if I were to have the idea of React, implementing in a way that is actually usable would be difficult. The key idea of React.js is that -- surprisingly -- it is possible to write efficient client-side code that describes how to render the application purely as a function of its state.

React is different than jQuery. With jQuery, you write lots of code explaining how to transform the user interface of your application from one complicated state (that you might never have anticipated happening) to another complicated state. When using React.js you don't write code about how your application's visible state changes -- instead you write code to answer the question: "given this state, what should the application look like". For me, it's a game changer. This is like what one does when writing video games; the innovation is that some people at Facebook figured out how to practically program this way in a client side web browser application, then tuned their implementation based on huge amounts of real world data (Facebook has users). Oh, and they open sourced the result and ran several conferences explaining React.

React.js reminds me of when Andrew Wiles proved Fermat's Last Theorem in the mid 1990s. Wiles (and Ken Ribet) had genuine new ideas, which dramatically reshaped the landscaped of number theory. The best number theorists quickly realized this and adopted to the new world, pushing the envelope of Wiles work far beyond what I expected could happen. Other people pretended like Wiles didn't exist and continued studying Fibonnaci numbers. I browsed the web development section of Barnes and Noble last night and there were dozens of books on jQuery and zero on React.js. I feel for anybody who tries to learn client-side web development by reading books at Barnes and Noble.

IPython/Jupyter and PhosphorJS I recently met with Fernando Perez, who founded IPython/Jupyter. He seemed to tell me that currently 9 people are working fulltime on rewriting the Jupyter web notebook using the PhosphorJS framework. I tried to understand PhosphorJS based on the github page, but couldn't, except to deduce that it is mostly the work of one person from Bloomberg/Continuum Analytics. Fernando told me that they chose PhosphorJS since it very fast, and that their main motivation is to (1) make Jupyter better use their huge high-resolution monitors on their new institute at Berkeley, and (2) make it easier for developers like me to integrate/extend Jupyter into their applications. I don't understand (2), because PhosphorJS is perhaps the least popular web framework I've ever heard of (is it a web framework -- I can't tell?). I pushed Fernando to explain why they made that design choice, but didn't really understand the answer, except that they had spent a lot of time investigating alternatives (like React first). I'm intimidated by their resources and concerned that I'm making the wrong choice; however, I just can't understand why they have made what seems to me to be the wrong choice. I hope to understand more at the joint Sage/Jupyter Days 70 that we are organizing together in Berkeley, CA in November.
Tables and RethinkDB Our rewrite of SMC is built on Tables, Flux and React. Tables are client-side technology I wrote inspired by Facebook's GraphQL/Relay technology (and Meteor, Firebase, etc.); they synchronize data between clients and the backend database in realtime. Tables are defined by a JSON schema file, which specifies the fields in the table, and explains what get and set queries are allowed. A table is a subset of a much larger table in the database, with the subset defined by conditions that are relative to the user making the query. For example, the projects table has one entry for each project that the user is a collaborator on.

Tables are automatically synchronized between the user and the database whenever the database changes, using RethinkDB changefeeds. RethinkDB's innovation is to build realtime updates -- triggered when the result of a query to the database changes -- directly into the database at the lowest level. Of course it is possible to build something that looks the same from the outside using either a message queue (say using RabbitMQ or ZeroMQ), or by watching the replication stream from the database and triggering actions based on that (like Meteor does using MongoDB). RethinkDB's approach seems better to me, putting the abstraction at the right level. That said, based on mailing list traffic, searches, etc., it seems that very, very few people get RethinkDB yet. Also, despite years of development, RethinkDB only became "production ready" a few months ago, and only got automatic failover a few weeks ago. That said, after ironing out some kinks, I'm now using it with heavy traffic in production and it works very well.

Once data is automatically synchronized between the database and web browsers in realtime, we can build everything else on top of this. Facebook also introduced an architecture pattern that they call Flux, which works well with React. It's very different than MVC-style two-way binding frameworks, where objects are directly linked to UI elements, with an object changing causing the UI element to change and vice versa. In SMC each major part of the system has two objects associated to it: Actions and Stores. We think of them in terms of the classical CQRS pattern -- command query responsibility segregation. Actions are commands -- they are Javascript "functions" that get stuff done, but they do not return values; instead, they impact the state of the store. The store has functions that allow one to query for the state of the store, but they do not change the state of the store. The store functions must only be functions of the internal state of the store and nothing else. They might cache their results and format their output to be very convenient for rendering. But that's it.

Actions usually cause the corresponding store (or stores) to change. When a store changes, it emit a change event, which causes any React components that depend on the store to be updated, which in many cases means they are re-rendered. There are optimizations one can introduce to reduce the amount of re-rendering, which if one isn't careful leads to subtle bugs; pretty much the only subtle React UI bugs one hits are caused by such optimizations. When the UI re-renders, the user sees their view of the world change. The user then clicks buttons, types, etc., which triggers actions, which in turn update stores (and tables, hence propogating changes to the ultimate source of truth, which is the RethinkDB database). As stores update, the UI again updates, etc.

Status So far, we have completely (re-)written the project listing, file manager, help/status page, new file page, project log, file finder, project settings, course management system, account settings, billing, project upgrade system, and file use notifications using React, Flux, and Tables, and the result works well. Bugs are much easier to fix, and it is easy (possible?) to understand the state of the system, since it is defined by the state of the database and the corresponding client-side stores. We've completely rethought everything about the UI in doing the rewrite of the above components, and it has taken several months. Also, as mentioned above, I completely rewrote most of the backend to use RethinkDB instead of Cassandra. There were also the weeks of misery for me after we made the switch over. Even after weeks of thinking/testing/wondering "what could go wrong?", we found out all kinds of surprising little things within hours of pushing everything into production, which took more than a week of sleep deprived days to sort out.

What's left? We have to rewrite the file editor tabs system, the project tabs system, and all the applications (except course management): editing text files using Codemirror, task lists (which are suprisingly complicated!), color xterm terminals, Jupyter notebooks (which will still use an iframe for the notebook itself), Sage worksheets (with complicated html output embedded in codemirror), compressed file de-archiver, the LaTeX editor, the wiki and markdown editors, and file chat. We hope to find a clean way to abstract away the various SMC applications as plugins, so that other people can easily write their own applications/plugins that will run inside of SMC. There will be a rich collection of example plugins to build on, namely the ones listed above, which are all driven by critical-to-us real world applications.

Closure Compiler parses JavaScript, removes dead code, minimizes what's left

31 August 2015 - 11:51am
What is the Closure Compiler?

The Closure Compiler is a tool for making JavaScript download and run faster. It is a true compiler for JavaScript. Instead of compiling from a source language to machine code, it compiles from JavaScript to better JavaScript. It parses your JavaScript, analyzes it, removes dead code and rewrites and minimizes what's left. It also checks syntax, variable references, and types, and warns about common JavaScript pitfalls.

How can I use the Closure Compiler?

You can use the Closure Compiler as:

Android Wear now works with iPhones

31 August 2015 - 11:43am

Today, Android Wear for iOS works with the LG Watch Urbane. All future Android Wear watches, including those from Huawei (pictured above), Asus, and Motorola will also support iOS, so stay tuned for more.

Dr. Seuss once said: “Today you are You, that is truer than true. There is no one alive who is Youer than You.” We agree. So whoever You are, and whatever You like—Android Wear lets you wear what you want.

Posted by David Singleton, Director of Engineering, Android Wear ]]>

When you wear something every day, you want to be sure it really works for you. That’s why Android Wear offers countless design choices, so you can find the watch that fits your style. Want a round watch with a more classic look? Feel like a new watch band? How about changing things up every day with watch faces from artists and designers? With Android Wear you can do all of that. And now, Android Wear watches work with iPhones.

Android Wear for iOS is rolling out today. Just pair your iPhone (iPhone 5, 5c, 5s, 6, or 6 Plus running iOS 8.2+) with an Android Wear watch to bring simple and helpful information right to your wrist:

  • Get your info at a glance: Check important info like phone calls, messages, and notifications from your favorite apps. Android Wear features always-on displays, so you’ll never have to move your wrist to wake up your watch.
  • Follow your fitness: Set fitness goals, and get daily and weekly views of your progress. Your watch automatically tracks walking and running, and even measures your heart rate.
  • Save time with smart help: Receive timely tips like when to leave for appointments, current traffic info, and flight status. Just say “Ok Google” to ask questions like “Is it going to rain in London tomorrow?” or create to-dos with “Remind me to pack an umbrella.”


Today, Android Wear for iOS works with the LG Watch Urbane. All future Android Wear watches, including those from Huawei (pictured above), Asus, and Motorola will also support iOS, so stay tuned for more.

Dr. Seuss once said: “Today you are You, that is truer than true. There is no one alive who is Youer than You.” We agree. So whoever You are, and whatever You like—Android Wear lets you wear what you want.

Posted by David Singleton, Director of Engineering, Android Wear

Google OnHub Review

31 August 2015 - 10:19am

The lowly router is a necessary evil. It’s a device we can’t live without, but often feels like an arcane relic from an era when boxy tube monitors and dial-up modems ruled. The router is the gateway to high-speed internet in our homes, and it enables us to wirelessly connect countless gadgets — smartphones, laptops, TVs, thermostats, speakers, coffee makers, game consoles, the list goes on — to the internet. It’s only going to get more important as more and more appliances rely on Wi-Fi connectivity for modern conveniences.

As important as they are, routers are equally notorious for being unattractive, difficult to set up, unreliable, and generally unpleasant to use. Most people use the router provided to them by their internet service provider (ISP), which may have terrible wireless range and a ridiculously complex setup process. Aftermarket routers, whether it be a model from Netgear, Asus, or even Apple, can provide better coverage and wireless range, but even those aren’t the easiest things to set up or manage.

Google is attempting to flip that paradigm on its head with its new line of OnHub Wi-Fi routers. The first OnHub router is a $199 model manufactured by TP-Link to Google’s design and specifications. It's shipping this week and doesn’t look anything like a traditional router. A sleek cylinder with a matte blue or black finish, the OnHub ditches the traditional array of blinking lights for a single glowing status ring, and is something you could put anywhere in your house without much embarrassment. And the OnHub doesn’t just look good: it’s packed with powerful antennas to ensure optimal wireless coverage and throughput throughout your home. It’s all controlled with an easy-to-use app, making setup and troubleshooting much easier than with traditional routers.

With the OnHub, Google is trying to solve the three biggest pain points of routers — setup, coverage, and troubleshooting — and build a wireless portal for the future. Did it also happen to create the perfect router? After switching out my current router and using the OnHub for the past few days in my own home, I want to say that Google has come awfully close, with just a couple of downsides that may or may not matter to you.

Google is spending a lot of its marketing efforts around the OnHub talking about its design, and rightly so. The OnHub doesn’t look like any traditional router, save for perhaps Apple’s AirPort Extreme. It’s a sleek cylinder with no protruding antennas, lighting arrays, or ISP logos. All of that is for a reason: Google wants you to place the OnHub centrally in your home, which is the most ideal position for wireless coverage and range. To get most people to do that, it can’t look like something that dropped out of an alien spacecraft.

The OnHub doesn't look like it fell out of an alien spacecraft

Google’s point of centrally locating the OnHub in your home is valid: if it’s the same distance from every room in the house, wireless coverage is maximized to its full potential. Walls, furniture, appliances, and all of the normal stuff people have in their homes can block Wi-Fi signals, so having fewer of those in the way makes for a better experience. But the problem with this ideal concept is that most people’s broadband modem often isn’t in the center of the home. The OnHub has to be plugged into the modem in order to access the internet, making it extremely difficult to put it in a different physical location than your modem. Fortunately, the OnHub’s powerful wireless range made this a non-issue: I put it upstairs in my home office next to my cable modem, where my prior router was located. (More on wireless coverage later.)

Setting up the OnHub in my home was painless: I plugged it in, downloaded the app to my smartphone (OnHub has apps for Android and iOS), and went through the setup process. That involves holding my phone near the router to pair it via audio signal and start the initial configuration, which is a lot easier than trying to directly connect my phone to a temporary wireless network or pair it over Bluetooth. All in all, I was up and running in less than five minutes, including naming my network and picking a password that I could easily remember.

Even after you’ve set it up, you still might actually find yourself opening the OnHub’s mobile app. It makes it incredibly easy to see what devices are connected to your network and which ones are using the most bandwidth. You can prioritize bandwidth to specific devices, so if you’re having an online gaming session or want to stream 4K content to your TV, you can allocate the most bandwidth to those tasks. Rebooting the router is also done right from the app, as is updating its firmware, which Google says happens automatically. You can also share the network’s password with a friend just by showing them a screen from the app.

Setup and troubleshooting are all done through the app

It also lets you run speed tests — both from your ISP to your modem and from the OnHub to your wireless devices — making it easy to identify where a bottleneck might be occurring. The app even tells you what your speed enables you to do: whether that’s stream ultra HD 4K content or something less bandwidth-intensive, giving actual meaning to the upload and download numbers.

One last thing: Google stridently denies that it’s tracking any of your activity on the internet with this router. It also says that the OnHub will work with any ISP, though your ISP might try to convince you that only its router works with its service.

A dimmable LED ring is the only indicator light on the OnHub

Prior to the OnHub, I had been using an Asus RT-AC66U dual-band wireless router in my modest, two-story, four-bedroom home. The Asus cost me about $200 and is a highly-rated router, with configurable antennas, 2.4GHz and 5GHz network support, and lots of settings and options. At any given time, I would have a dozen or more devices connected to it, including smartphones, tablets, speakers, set top boxes, laptops, lightbulbs, and smoke detectors. But despite its cost and feature set, the Asus still needed the help of a wireless repeater to provide coverage in my downstairs bedroom. Other parts of the home had dead or extremely slow zones, and the video monitor we use for watching our infant would completely interfere with the 2.4GHz network, rendering it unusable.

My expectations for the OnHub were thusly set: I was sure that placing it in my office would result in a similar experience I had with the Asus (and I wasn’t interested in piping Ethernet wires throughout my home to put it in a different spot). But I’ve had zero issues with the OnHub: coverage has been shockingly good, I haven’t needed to use the wireless repeater at all, and the interference I saw with the baby monitor has disappeared. In areas that were formerly dead zones, the OnHub has given me enough bandwidth and throughput to stream 4K video, even in my basement, a full two stories below my office. This is despite putting the router in a less-than-ideal location: upstairs, in my office, far from our general living areas.

Coverage and throughput are shockingly good

To make that happen, the OnHub employs a total of 13 internal antennas: six for its 2.4GHz network, six for 5GHz, and one to monitor the network and automatically tune the radios to the best settings. Google says the antennas are arranged within the OnHub for the best possible coverage regardless of how the router itself is positioned. The front-facing 2.4GHz antenna has also been custom designed with a special reflector to boost coverage in that direction.

All of that means I didn’t have to do anything to optimize the radio coverage (nor could I, really). I just put the OnHub in my office, set it up, and went about my life. Unlike a lot of routers, the OnHub doesn’t broadcast separate 2.4GHz and 5GHz networks. Instead, the same network name (or SSID) covers both frequencies, and the OnHub will dynamically adjust network depending on which frequency offers the best blend of coverage, speed, and minimal interference. (Typically, 2.4GHz networks have broader range, while 5GHz ones have higher throughput and less interference from other devices, such as my baby monitor.) That makes it easy when adding a device to the network: there’s only one option to choose from and one password you need to input.

There are a couple of things that make the OnHub less than perfect, and they center around Google’s oversimplified design. The OnHub only has one Ethernet LAN port, which was quickly filled by my Philips Hue, leaving me no other ports to plug in any other smart home gadget that requires a dedicated hub or use a wired connection with my desktop computer. To get more ports, I’d have to purchase and use a network hub, which adds another level of cost and complexity that the OnHub was designed to eliminate. There’s also only one USB port on the OnHub, making it impossible to use both a media server and a backup hard drive at the same time.

Ethernet jacks and USB ports are limited on the OnHub

Most of those complaints are power-user issues, I admit, but they are features that buyers of $200 routers have come to expect. Google says this OnHub is only the first in a line, however. Future models from other manufacturers, including Asus, are coming later on. It’s certainly possible that those models could include more USB and Ethernet ports, though there’s no guarantee that they will or how much they might cost if they do.

Google also says the OnHub is set up for future smarthome products, including its own forthcoming Weave platform, and it has built-in Bluetooth and Zigbee radios that are not currently enabled. The company claims that it will be improving the OnHub over time with more features and capabilities via firmware updates, but beyond adding the aforementioned smarthome support, it’s not clear what exactly those upgrades will offer. One thing that doesn’t seem possible with this model is Amazon Echo-like functionality: the OnHub has a speaker, but lacks a microphone, making it unable to respond to voice controls.

Of course, the million-dollar (or $199) question here is: do you really need to spend this much on a wireless router when you can get one for free from your ISP or choose a basic third-party option for as little as $50? Many of my colleagues balked at the price of the OnHub when it was announced a couple of weeks ago, but as someone who’s already been down the road of buying a high-end router to cover my home, I can easily see its value. If you live in a small apartment, chances are you don’t need the power the OnHub offers (though perhaps you could benefit from its simplicity and app-based control). But for any modest sized or larger home, the benefits of the OnHub are readily apparent: it just works better than any other router I’ve used, whether that was provided by my ISP or purchased separately.

The humble router has been important for years and will be increasingly important as more and more products add Wi-Fi features. A few years from now, things such as a Wi-Fi-enabled toaster, washing machine, door bell, or garage door opener won’t be the domain of early adopters, they will be commonplace. All of them require a solid Wi-Fi network and strong router powering that network. The OnHub may not be the first router designed specifically with that future in mind, but it’s by far the best option right now.

The OnHub does its job with no fuss or attention needed from me

Like most appliances, the router is supposed to be invisible, do its job, and stay out of your way. For the first time, I can say my router does just that — I don’t have to worry about whether or not my Wi-Fi is working with the OnHub because it just does. Google has a grander ambition for the OnHub and its followup products, but even if that never comes to fruition, having usable Wi-Fi anywhere in my home is worth the $199 to me.