Measuring Web Latency In The Browser

July 21, 2018 by Tom Nardi 8 Comments

We’ll go out on a limb and assume that anyone reading these words is probably familiar with the classic ping command. Depending on which operating system you worship the options might be slightly different, but every variation of this simple tool does the same thing: send an ICMP echo request and wait for a response. How long it takes to get a response from the target, if it gets one at all, is shown to the user. This if often the very first step to diagnosing network connectivity issues; if this doesn’t work, there’s an excellent chance the line is dead.

But in the modern web-centric view of networking, ping might not give us the whole picture. But nature it doesn’t take into account things like DNS lookups, and it certainly doesn’t help you determine what (if any) services the target has available to you. Accordingly, [Liu Zhiyong] has come up with a tool he calls “pingms”, which allows you to check web server latency right from your browser.

Rather than relying on ICMP, pingms performs a more realistic test. It takes the list of targets from the file “targets.js” and connects to each one over HTTP. How does it work? The code [Liu] has come up with will take each target domain name, append a random number to create a gibberish filename, and then calculate how long it takes to get a response when trying to download the file. Obviously it’s going to be getting a 404 response from the web server, but the important thing is simply that it gets the response.

With this data, [Liu] has come up with a simplistic but very slick interface which shows the user the collected data with easy to understand color-coded graphs. As interesting as it is to see how long it takes your favorite web sites or service providers to wake up and start talking, watching the colored bars hop up and down the list to sort themselves is easily our favorite part of pingms.

[Liu] has released pingms under the GPLv3 license, so if you’re looking to utilize the software for your own purposes you just need to provide a list of test targets. If you need to perform low-level diagnostics, check out this handy network tester you can build for cheap.

Twitch Stream Turned Infinity Mirror

July 18, 2018 by Tom Nardi 6 Comments

Most Hackaday readers are likely to be familiar with the infinity mirror, a piece of home decor so awesome that Spock still has one up on the wall in 2285. The idea is simple: two parallel mirrors bounce and image back and forth, which creates a duplicate reflection that seems to recede away into infinity. A digital version of this effect can be observed if you point a webcam at the screen that’s displaying the camera’s output. The image will appear to go on forever, and the trick provided untold minutes of fun during that period in the late 1990’s where it seemed everyone had a softball-shaped camera perched on their CRT monitors.

While you might think you’ve already seen every possible variation of this classic visual trick, [Matt Nishi-Broach] recently wrote in to tell us about an infinity mirror effect he’s created using the popular streaming platform Twitch. The public is even invited to fiddle with the visuals through a set of commands that can be used in the chat window.

It works about how you’d expect: the stream is captured, manipulated through various filters, and then rebroadcast through Twitch. This leads to all sorts of weird visual effects, but in general gives the impression that everything is radiating from a central point in the distance.

While [Matt] acknowledges that there are probably not a lot of other people looking to setup their own Twitch feedback loops, he’s still made his Python code available for anyone who might be interested. There’s a special place in Hacker Valhalla for those who release niche software like this as open source. They’re the real MVPs.

If you’d like to get started on your infinite journey with something a bit more physical, we’ve covered traditional infinity mirror builds ranging from the simplistic to the gloriously over-engineered.

Quantum Computing For Computer Scientists

July 13, 2018 by Al Williams 16 Comments

Quantum computing is coming, so a lot of people are trying to articulate why we want it and how it works. Most of the explanations are either hardcore physics talking about spin and entanglement, or very breezy and handwaving which can be useful to get a little understanding but isn’t useful for applying the technology. Microsoft Research has a video that attempts to hit that spot in the middle — practical information for people who currently work with traditional computers. You can see the video below.

The video starts with basics you’d get from most videos talking about vector representation and operations. You have to get through about 17 minutes of that sort of thing until you get into qubits. If you glaze over on math, listen to the “index array” explanations [Andrew] gives after the math and you’ll be happier.

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Simple Quadcopter Testbed Clears The Air For Easy Algorithm Development

June 28, 2018 by Ben James 1 Comment

We don’t have to tell you that drones are all the rage. But while new commercial models are being released all the time, and new parts get released for the makers, the basic technology used in the hardware hasn’t changed in the last few years. Sure, we’ve added more sensors, increased computing power, and improved the efficiency, but the key developments come in the software: you only have to look at the latest models on the market, or the frequency of Git commits to Betaflight, Butterflight, Cleanflight, etc.

With this in mind, for a Hackaday prize entry [int-smart] is working on a quadcopter testbed for developing algorithms, specifically localization and mapping. The aim of the project is to eventually make it as easy as possible to get off the ground and start writing code, as well as to integrate mapping algorithms with Ardupilot through ROS.

The initial idea was to use a Beaglebone Blue and some cheap hobby hardware which is fairly standard for a drone of this size: 1250 kv motors and SimonK ESCs, mounted on an f450 flame wheel style frame. However, it looks like an off-the-shelf solution might be even simpler if it can be made to work with ROS. A Scanse Sweep LIDAR sensor provides point cloud data, which is then munched with some Iterative Closest Point (ICP) processing. If you like math then it’s definitely worth reading the project logs, as some of the algorithms are explained there.

It might be fun to add FPV to this system to see how the mapping algorithms are performing from the perspective of the drone. And just because it’s awesome. FPV is also a fertile area for hacking: we particularly love this FPV tracker which rotates itself to get the best signal, and this 3D FPV setup using two cameras.

Keep It Close: A Private Git Server Crash Course

June 27, 2018 by Tom Nardi 65 Comments

At this point, everyone has already heard that Microsoft is buying GitHub. Acquisitions of this scale take time, but most expect everything to be official by 2019. The general opinion online seems to be one of unease, and rightfully so. Even if we ignore Microsoft’s history of shady practices, there’s always an element of unease when somebody new takes over something you love. Sometimes it ends up being beneficial, the beginning of a new and better era. But sometimes…

Let’s not dwell on what might become of GitHub. While GitHub is the most popular web-based interface for Git, it’s not the only one. For example GitLab, a fully open source competitor to GitHub, is reporting record numbers of new repositories being created after word of the Microsoft buyout was confirmed. But even GitLab, while certainly worth checking out in these uncertain times, might be more than you strictly need.

Let’s be realistic. Most of the software projects hackers work on don’t need even half the features that GitHub/GitLab offer. Whether you’ve simply got a private project you want to maintain revisions of, or you’re working with a small group collaboratively in a hackerspace setting, you don’t need anything that isn’t already provided by the core Git software.

Let’s take a look at how quickly and easily you can setup a private Git server for you and your colleagues without having to worry about Microsoft (or anyone else) having their fingers around your code.

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Conquering The Earth With Cron

June 25, 2018 by Tom Nardi 15 Comments

The GOES-R series of Earth observation satellites are the latest and greatest NASA has to offer. As you might expect, part of the GOES-R job description is imaging Earth at high-resolution, but they also feature real-time lighting monitoring as well as enhanced solar flare and space weather capabilities. Four of these brand new birds will be helping us keep an eye on our planet’s condition into the 2030s. Not a bad way to spend around 11 billion bucks.

To encourage innovation, NASA is making the images collected by the GOES-R satellites available to the public through a collaboration with Google Cloud Platform. [Ben Nitkin] decided to play around with this data, and came up with an interactive website that let’s you visualize the Earth from the perspective of GOES-R. But don’t let those slick visuals fool you, the site is powered by a couple cron jobs and some static HTML. Just as Sir Tim Berners-Lee intended it.

But it’s not quite as easy as scheduling a wget command; the images GOES-R collects are separated into different wavelengths and need to be combined to create a false-color image. A cron job fires off every five minutes which downloads and merges the raw GOES-R images, and then another cron job starts a Python script that creates WebM time-lapse videos out of the images using ffmpeg. All of the Python scripts and the crontab file are available on GitHub.

Finally, with the images merged and the videos created, the static HTML website is served out to the world courtesy of a quick and dirty Python web server. The site could be served via something more conventional, but [Ben] likes to keep overhead as low as possible.

If you want to take the more direct route, we’ve covered plenty of projects focused on pulling down images from weather satellites; from using old-school “rabbit ears” to decoding the latest Russian Meteor-M N2 downlink.

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A Real Time Data Compression Technique

June 25, 2018 by Al Williams 41 Comments

With more and more embedded systems being connected, sending state information from one machine to another has become more common. However, sending large packets of data around on the network can be bad both for bandwidth consumption and for power usage. Sure, if you are talking between two PCs connected with a gigabit LAN and powered from the wall, just shoot that 100 Kbyte packet across the network 10 times a second. But if you want to be more efficient, you may find this trick useful.

As a thought experiment, I’m going to posit a system that has a database of state information that has 1,000 items in it. It looks like an array of RECORDs:

typedef struct
{
  short topic;
  int data;
} RECORD;

It doesn’t really matter what the topics and the data are. It doesn’t really matter if your state information looks like this at all, really. This is just an example. Given that it is state information, we are going to make an important assumption, though. Most of the data doesn’t change frequently. What most and frequently mean could be debated, of course. But the idea is that if I’m sending data every half second or whatever, that a large amount isn’t going to change between one send and the next.

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