{"id":13379,"date":"2021-12-09T21:08:01","date_gmt":"2021-12-10T02:08:01","guid":{"rendered":"https:\/\/carleton.ca\/scs\/?page_id=13379"},"modified":"2026-06-02T14:59:23","modified_gmt":"2026-06-02T18:59:23","slug":"tr-13-02-on-optimal-budget-driven-scheduling-algorithms-for-mapreduce-jobs-in-the-heterogeneous-cloud","status":"publish","type":"page","link":"https:\/\/carleton.ca\/scs\/research\/scs-technical-reports\/technical-reports-2013\/tr-13-02-on-optimal-budget-driven-scheduling-algorithms-for-mapreduce-jobs-in-the-heterogeneous-cloud\/","title":{"rendered":"TR-13-02: On Optimal Budget-Driven Scheduling Algorithms for MapReduce Jobs in the Heterogeneous Cloud"},"content":{"rendered":"\n<section class=\"w-screen px-6 cu-section cu-section--white ml-offset-center md:px-8 lg:px-14\">\n    <div class=\"space-y-6 cu-max-w-child-5xl  md:space-y-10 cu-prose-first-last\">\n\n            <div class=\"cu-textmedia flex flex-col lg:flex-row mx-auto gap-6 md:gap-10 my-6 md:my-12 first:mt-0 max-w-5xl\">\n        <div class=\"justify-start cu-textmedia-content cu-prose-first-last\" style=\"flex: 0 0 100%;\">\n            <header class=\"font-light prose-xl cu-pageheader md:prose-2xl cu-component-updated cu-prose-first-last\">\n                                    <h1 class=\"cu-prose-first-last font-semibold !mt-2 mb-4 md:mb-6 relative after:absolute after:h-px after:bottom-0 after:bg-cu-red after:left-px text-3xl md:text-4xl lg:text-5xl lg:leading-[3.5rem] pb-5 after:w-10 text-cu-black-700 not-prose\">\n                        TR-13-02: On Optimal Budget-Driven Scheduling Algorithms for MapReduce Jobs in the Heterogeneous Cloud\n                    <\/h1>\n                \n                                \n                            <\/header>\n\n                    <\/div>\n\n            <\/div>\n\n    <\/div>\n<\/section>\n\n<p>Carleton University<br>\n<a href=\"https:\/\/carleton.ca\/scs\/research\/scs-technical-reports\/technical-reports-2013\/\">Technical Report<\/a> TR-13-02<br>\nJune 28, 2013<\/p>\n\n\n\n<h2 id=\"on-optimal-budget-driven-scheduling-algorithms-for-mapreduce-jobs-in-the-heterogeneous-cloud\" class=\"wp-block-heading\">On Optimal Budget-Driven Scheduling Algorithms for MapReduce Jobs in the Heterogeneous Cloud<\/h2>\n\n\n\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">\n<div class=\"tr_t3\">Yang Wang &amp; Wei Shi<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div>\n<h3>Abstract<\/h3>\n<p>In this paper, we consider task-level scheduling algorithms with res-pect to budget and deadline constraints for a bag of MapReduce jobs on a set of provisioned heterogeneous (virtual) machines in cloud platforms. Heterogeneity is manifested in the \u201dpay-as-you-go\u201d charging model we use, where service machines with different performance have different service rates. We organize the bag of jobs as a \u03ba-stage workflow and achieve, for specific optimization goals, the following results. First, given a total monetary budget Bj&nbsp;for a particular stage j, we propose a greedy algorithm for distributing the budget, with minimal stage execution time as our goal. Based on the structure of this problem, we further prove the optimality of our algorithm in terms of the budget used and the execution time achieved. We then combine this algorithm with dynamic programming techniques to propose an optimal scheduling algorithm that obtains a minimum scheduling length in O(\u03baB2). The algorithm is efficient if the total budget B is polynomially bounded by the number of tasks in the MapReduce jobs, which is usually the case in practice. Second, we consider the dual of this optimization problem to minimize the cost when the (time) deadline of the computation D is fixed. We convert this problem into the standard multiplechoice knapsack problem via a parallel transformation. Our empirical studies verify the proposed optimal algorithms.<\/p>\n<p><a href=\"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/sites\/260\/TR-13-02-Shi.pdf\">TR-13-02.pdf<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Carleton University Technical Report TR-13-02 June 28, 2013 On Optimal Budget-Driven Scheduling Algorithms for MapReduce Jobs in the Heterogeneous Cloud Yang Wang &amp; Wei Shi Abstract In this paper, we consider task-level scheduling algorithms with res-pect to budget and deadline constraints for a bag of MapReduce jobs on a set of provisioned heterogeneous (virtual) machines [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":12514,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_cu_dining_location_slug":"","footnotes":"","_links_to":"","_links_to_target":""},"cu_page_type":[],"class_list":["post-13379","page","type-page","status-publish","hentry"],"acf":{"cu_post_thumbnail":false},"_links":{"self":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/13379","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/comments?post=13379"}],"version-history":[{"count":2,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/13379\/revisions"}],"predecessor-version":[{"id":13381,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/13379\/revisions\/13381"}],"up":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/12514"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/media?parent=13379"}],"wp:term":[{"taxonomy":"cu_page_type","embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/cu_page_type?post=13379"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}