Archive for the ‘Location’ Category

File Under: Backend, Location, servers, Web Basics
Aug
31
2011

OpenDNS and Google Working with CDNs on DNS Speedup

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A group of DNS providers and content delivery network (CDN) companies have devised a new extension to the DNS protocol that that aims to more effectively direct users to the closest CDN endpoint. Google, OpenDNS, BitGravity, EdgeCast, and CDNetworks are among the companies participating in the initiative, which they are calling the Global Internet Speedup.

The new DNS protocol extension, which is documented in an IETF draft, specifies a means for including part of the user’s IP address in DNS requests so that the nameserver can more accurately pinpoint the destination that is topologically closest to the user. Ensuring that traffic is directed to CDN endpoints that are close to the user could potentially reduce latency and congestion for high-impact network services like video streaming.

The new protocol extension has already been implemented by OpenDNS and Google’s Public DNS. It works with the CDN services that have signed on to participate in the effort. Google and OpenDNS hope to make the protocol extension an official IETF standard. Other potential adopters—such as Internet ISPs—are free to implement it from the draft specification.

It’s not really clear in practice how much impact this will have on network performance. It’s worth noting that GeoIP lookup technology is already used by some authoritative DNS servers for location-aware routing. The new protocol extension will reportedly address some of the limitations of previous approaches.

This article originally appeared on Ars Technica, Wired’s sister site for in-depth technology news.

File Under: Frameworks, Location, Programming
Mar
1
2011

Who Swears the Most? How Foursquare Used Hadoop to Find Out

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We told you who swears the most in their code, but what about in the real world? Foursquare, the location check-in service, has used its rather large dataset to graph the “rudest” places in the English-speaking world — Manchester, U.K. takes top honors.

While the results should be taken with a grain of salt — after all the swearing is limited to Foursquare users and there’s no hint of what constitutes a swear word — the methods Foursquare used to get the data make a great intro to the world of Apache Hadoop and Apache Hive.

Hadoop is an open-source MapReduce framework — a way of processing huge datasets stored in large server clusters (or grids). While MapReduce frameworks were originally introduced by Google (which has very large datasets to work with) they’ve since grown beyond Google and their usefulness isn’t limited to large companies with massive databases.

In fact, with Amazon’s Elastic MapReduce just about anyone can easily and cheaply run their own Hadoop framework and process vast amounts of data just like Google does.

Because word search processing is generally considered the canonical example of what makes a MapReduce framework useful, Foursquare’s blog post offers a good overview of how you can use MapReduce to mine through anything from large text documents to user-contributed data like the check-in snippets Foursquare is processing.

Foursquare’s server setup is specific to them, but there’s one key element that’s worth bearing in mind — store your Hadoop data well away from your production system. MapReduce doesn’t work at the speed of the web and you don’t want it dragging your site down.

In Foursquare’s case that means using Amazon’s Elastic MapReduce plus a simple Ruby on Rails server. The result is, as Foursquare Engineer Matthew Rathbone puts it, “a powerful (and cheap) data analysis tool.”

If you’re new to MapReduce and functional programming in general, read through the Foursquare post for an overview on how MapReduce is useful and then check out the Hadoop site, as well as this overview video from Cloudera.

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File Under: Location
Mar
1
2011

Google Street View, Coming Soon to a Living Room Near You

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Google Street View inside the San Diego Art Institute gardens

It’s time for Google to rename its Street View feature. Google Maps’ Street View is no longer limited to streets, the company is now using tricycles to photograph off-road locations like the gardens at the San Diego Art Institute or Château de Chenonceaux in Civray-de-Touraine, France.

Google has been using the modified trikes — which house a 360° panoramic camera much like the setup on the Street View cars, but smaller and lighter — since 2009. Google previously released imagery the trikes captured in places like Stonehenge and Sea World.

Combine the latest update with Google’s previous release of Street View inside buildings and it isn’t hard to imagine that, in the future, Street View may well be in your living room.

In fact, you may be the one who puts Street View in your living room. Last year Google acquired Quiksee, an app that takes normal video input and produces video tours — much like Street View, but with no special camera required. Although Google has made no announcements since the acquisition, it’s not hard to imagine the company releasing some software that allows anyone to create Street View-like images of, well, just about anywhere.

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File Under: Location, Web Apps, Web Services
Nov
30
2010

Mining Flickr to Build 3D Models of the World

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Microsoft’s PhotoSynth tool is jaw-droppingly awesome. But, because it’s a Microsoft project, the technology is unlikely to appear on some of your favorite non-Microsoft online apps, like Google Maps or Flickr.

However, our friends at ReadWriteWeb stumbled across a very similar tool — at least in terms of the end result — developed by the University of North Carolina in conjunction with Swiss university, ETH-Zurich.

The team has developed a method for creating 3D models by pulling in millions of photographs from Flickr and using some fancy algorithms to generate 3D models of local landmarks. Perhaps even more impressive the results can be generated using a single computer in under a day.

Project lead Jan-Michael Frahm touts the project’s efficiency saying, “our technique would be the equivalent of processing a stack of photos as high as the 828-meter Dubai Towers, using a single PC, versus the next best technique, which is the equivalent of processing a stack of photos 42 meters tall — as high as the ceiling of Notre Dame — using 62 PCs. This efficiency is essential if one is to fully utilize the billions of user-provided images continuously being uploaded to the internet.”

While the results are cool and would make an impressive addition to any number of geo-based services, more serious use cases include helping disaster workers get a better idea of where they’re headed and the extent of damage.

So far the researchers have released a movies demonstrating the technique on landmarks in both Rome (get it? built in a day…) and Berlin, and the results are impressive. For more information on how the process works, check out the UNC website.

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File Under: Location, Social
Nov
16
2010

Google Hotpot Smartens Up Local Search, But It’s No Yelp Killer

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Google has unveiled the awkwardly-named Hotpot, which is a kind of ratings tool and recommendation engine for Google Places.

As you review restaurants, music venues, stores and the like, Hotpot’s recommendation engine learns what you like and suggests other places you might like. Throw in recommendations from friends and Hotpot starts to sound very useful. Indeed Hotpot is useful, bringing location-based searching, algorithms that learn what you like and friends’ recommendations together in a single place.

But, perhaps because of that combination of features, it’s also awkward to set up and poorly integrated with the rest of Google’s services. It has some features that trump its main competitor, Yelp, like the awesome search tool. But the social and community aspects of Hotpot — features Yelp handles well — are too difficult to get set up.

Which isn’t to say that Hotpot isn’t useful. You just have to clear its awkward silo-style hurdles first. If you head over to the new Hotpot URL, you’ll be asked to sign in with your Google account and then to pick a nickname for use on Google Places.

Once that’s done you’ll need to find your friends and “add” then to your list of Hotpot friends. Setting up Hotpot feels a bit like you just slipped back in time five years to a web where every social service is an island.

It could be that Google was worried about another Buzz-style backlash if it made Hotpot’s social features automated. Instead, everything is manual — you’re presented with a list of friends that you can add (follow might be the more familiar verb here) much like the process Google Reader uses.

However, with Reader the sharing notices are sent inside the Reader web app. With Hotpot, the notices are sent to your friend’s Gmail account for approval. Worse, there doesn’t seem to be an “Add all” button — if you’ve got 300 friends, you’ll be click “Add” 300 times.

Once you’ve made it past the initial hurdles of setting Hotpot up, its results are actually pretty good. Having only tested Hotpot for a few hours, it’s hard to judge the quality of recommendations, but as a simple Google Places search tool, the interface is clean and easy to use.

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