{"id":192441,"date":"2015-06-29T00:00:00","date_gmt":"2015-06-29T12:33:23","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/energy-efficient-scheduling-in-the-non-clairvoyant-model\/"},"modified":"2016-07-15T15:24:39","modified_gmt":"2016-07-15T22:24:39","slug":"energy-efficient-scheduling-in-the-non-clairvoyant-model","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/energy-efficient-scheduling-in-the-non-clairvoyant-model\/","title":{"rendered":"Energy-efficient Scheduling in the Non-clairvoyant Model"},"content":{"rendered":"<div class=\"asset-content\">\n<p>A fundamental problem in energy-efficient computing is to schedule multiple jobs released over time on a single machine with adjustable speed so as to minimize the sum of flow-time (delay) and energy. Note that the two objectives are in conflict: higher speeds reduce flow-time at the cost of increased energy consumption. In this talk, motivated by datacenter applications, I will consider the non-clairvoyant version of this problem where the density (importance) of a job is known when the job arrives but its volume (processing length) is known only after the job has been completely processed. Using a novel technique called incremental analysis, we  give a constant-competitive algorithm for this problem, which is the first non-trivial result for the non-clairvoyant setting. (Based on joint work with Yossi Azar, Nikhil Devanur, and Zhiyi Huang, recipient of the \u201cBest paper\u201d award in SPAA 2015.)<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A fundamental problem in energy-efficient computing is to schedule multiple jobs released over time on a single machine with adjustable speed so as to minimize the sum of flow-time (delay) and energy. Note that the two objectives are in conflict: higher speeds reduce flow-time at the cost of increased energy consumption. In this talk, motivated [&hellip;]<\/p>\n","protected":false},"featured_media":199112,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[206954],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-192441","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-video-type-microsoft-research-talks","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/eb4odgbZ-M8","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/192441","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/192441\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/199112"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=192441"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=192441"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=192441"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=192441"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=192441"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=192441"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=192441"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=192441"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=192441"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=192441"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}