|Test of Time Paper Award For Distributed Caching Algorithms|
|Written by Sue Gee|
|Friday, 15 July 2022|
A paper on distributed caching algorithms for content distribution networks authored by Sem Borst,Varun Gupta and Anwar Walid was selected to receive the 2022 IEEE INFOCOM Test of Time Paper Award for its “significant impact on the research community”.
Awards made at the annual IEEE International Conference on Computer Communications, which this year was a virtual event, included the Koji Kobayashi Computers and Communications Award which, as we recently reported went to Muriel Médard. The IEEE INFOCOM Test of Time Paper Award, which recognizes papers that have been most cited published in the INFOCOM proceedings between 10 and 12 years previously, a three-year window, was also presented at the event.
For 2022 the award committee selected “Distributed Caching Algorithms for Content Distribution Networks," which was presented at the 2010 conference. At the time the paper's three authors were engaged in research at the Alcatel-Lucent Bell Labs in Murray Hill. Now Sem Borst is professor of stochastic operations research at Eindhoven University of Technology, Varun Gupta is an associate professor of operations management at the University of Chicago and Anwar Walid is adjunct professor at Columbia Univeristy, senior editor for the IEEE Journal on Selected Areas in Communications and an Amazon applied science manager working in Amazon Ads where, among other things, his team builds machine learning models that predicts click-through rates for advertisements.
The problem addressed in the 2010 paper, a time when overall bandwidth demands were increasing by orders of magnitude, was how to improve the user experience given the sudden explosion of streaming video. Back then large video objects were stored in central servers that were often located far from users, which resulted in lengthy video download times as well as delays or interruptions in streaming videos to viewers. There were, however, opportunities in placing caches at different network provider locations. The paper details distributed algorithms for managing video caches, which temporarily store frequently accessed data close to the location of network user. Because video does not have to travel the entire length of the network, cache optimization helps accelerate the delivery of content. The algorithms adapt to the changing dynamics of content popularity and ingestion rate.
Over the last decade various caching solutions and enhanced proposals for online video content delivery have used the ideas explained in the paper as a foundation to newer approaches to improving the viewer experience.
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|Last Updated ( Friday, 15 July 2022 )|