{"id":5366,"date":"2019-10-26T15:06:40","date_gmt":"2019-10-26T17:06:40","guid":{"rendered":"http:\/\/nubo.ai\/?p=5366"},"modified":"2019-10-26T15:07:19","modified_gmt":"2019-10-26T17:07:19","slug":"interference-aware-scheduling-for-data-processing-frameworks-in-container-based-clusters","status":"publish","type":"post","link":"https:\/\/nubo.ai\/?p=5366","title":{"rendered":"Interference-aware Scheduling for Data-processing Frameworks in Container-based Clusters"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"5366\" class=\"elementor elementor-5366\" data-elementor-settings=\"[]\">\n\t\t\t<div class=\"elementor-inner\">\n\t\t\t\t<div class=\"elementor-section-wrap\">\n\t\t\t\t\t\t\t<section class=\"elementor-element elementor-element-67fb4b02 elementor-section-boxed elementor-section-height-default elementor-section-height-default elementor-section elementor-top-section\" data-id=\"67fb4b02\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t<div class=\"elementor-element elementor-element-16f4ec7 elementor-column elementor-col-100 elementor-top-column\" data-id=\"16f4ec7\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap  elementor-element-populated\">\n\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t<div class=\"elementor-element elementor-element-100db479 elementor-widget elementor-widget-text-editor\" data-id=\"100db479\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\"><p><strong>Abstract<\/strong><br \/>With the emergence of data-processing frameworks like Hadoop and Spark, a new concept of a cluster resource manager was necessary to deliver per-application containerwrapped on-demand resources with high scalability on a large scale. The container-based \u201dBig Data\u201d Operating System concept arose (e.g. YARN and Mesos) and brought along with it the long-standing inter-instance performance interference issues from virtualization technologies. As a result, the performance interference effects between co-located data-processing applications become an uncertain issue in container-based clusters, leading performance to fluctuate unpredictably and the guarantees to be likely violated. To work around this, an interference-aware scheduling algorithm is necessary to mitigate interference-related performance degradation and wisely schedule tasks on the bestsuited compute nodes\u2014the nodes whose performance is maximized and the makespan is minimized.<\/p>\n<p>http:\/\/www.pdsw.org\/pdsw-discs16\/wips\/xavier-wip-pdsw-discs16.pdf<\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"AbstractWith the emergence of data-processing frameworks like Hadoop and Spark, a new concept of a cluster resource manager was necessary to deliver per-application containerwrapped on-demand resources with high scalability on a large scale. The container-based \u201dBig Data\u201d Operating System concept arose (e.g. YARN and Mesos) and brought along with it the long-standing inter-instance performance interference&#8230;","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","footnotes":""},"categories":[49],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5366"}],"collection":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5366"}],"version-history":[{"count":3,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5366\/revisions"}],"predecessor-version":[{"id":5370,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5366\/revisions\/5370"}],"wp:attachment":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5366"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5366"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5366"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}