{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T12:21:37Z","timestamp":1765887697009,"version":"3.41.0"},"reference-count":20,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2015,6,2]],"date-time":"2015-06-02T00:00:00Z","timestamp":1433203200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGMETRICS Perform. Eval. Rev."],"published-print":{"date-parts":[[2015,6,2]]},"abstract":"<jats:p>Multi-resource sharing for concurrent workows necessitates a fairness criteria to allocate multiple resources to work-flows with heterogeneous demands. Recently, this problem has attracted increasing attention and has been investigated by assuming that each workow has a single class of jobs and that each class contains jobs of the same demand profile. The demand profile of a class represents the required multi-resources of a job. However, for typical applications in cloud computing and distributed data processing systems, a workow usually needs to process multiple classes of jobs. Relying on the concept of slowdown, we characterize fairness for multi-resource sharing and address scheduling for multiclass workows. We optimize the mixture of different classes of jobs for a workow as optimal operation points to achieve the least slowdown, and discuss desirable properties for these operation points. These studies assume that the jobs are infinitely divisible.<\/jats:p>\n          <jats:p>When jobs are non-preemptive and indivisible, any fairness criteria that only relies on the instantaneous resource allocation cannot be strictly maintained at every time point. To this end, we relax the instantaneous fairness to an average metric within a time interval. This relaxation introduces a time average to fairness and allows occasional, but not too often, violations of instantaneous fairness. In addition, it brings exibility and opportunities for further optimization on resource utilization, e.g., using bin-packing, within the constraint on fairness.<\/jats:p>","DOI":"10.1145\/2788402.2788408","type":"journal-article","created":{"date-parts":[[2015,6,3]],"date-time":"2015-06-03T15:35:55Z","timestamp":1433345755000},"page":"31-37","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Multi-resource Fair Sharing for Multiclass Workflows"],"prefix":"10.1145","volume":"42","author":[{"given":"Jian","family":"Tan","sequence":"first","affiliation":[{"name":"IBM T. J. Watson Research Center, NY"}]},{"given":"Li","family":"Zhang","sequence":"additional","affiliation":[{"name":"IBM T. J. Watson Research Center, NY"}]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"IBM T. J. Watson Research Center, NY"}]},{"given":"Yandong","family":"Wang","sequence":"additional","affiliation":[{"name":"IBM T. J. Watson Research Center, NY"}]}],"member":"320","published-online":{"date-parts":[[2015,6,2]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Hadoop. http:\/\/hadoop.apache.org\/.  Hadoop. http:\/\/hadoop.apache.org\/."},{"key":"e_1_2_1_2_1","unstructured":"Spark. http:\/\/spark.apache.org\/.  Spark. http:\/\/spark.apache.org\/."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2523616.2523637"},{"key":"e_1_2_1_4_1","volume-title":"Turin","author":"Bonald T.","year":"2014","unstructured":"T. Bonald and J. Roberts . Enhanced cluster computing performance through proportional fairness. pages 2--23 , Turin , Italy , October 2014 . T. Bonald and J. Roberts. Enhanced cluster computing performance through proportional fairness. pages 2--23, Turin, Italy, October 2014."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2090236.2090243"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2600057.2602889"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2377677.2377679"},{"key":"e_1_2_1_8_1","first-page":"323","volume-title":"Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation, NSDI'11","author":"Ghodsi A.","year":"2011","unstructured":"A. Ghodsi , M. Zaharia , B. Hindman , A. Konwinski , S. Shenker , and I. Stoica . Dominant resource fairness: Fair allocation of multiple resource types . In Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation, NSDI'11 , pages 323 -- 336 , Berkeley, CA, USA , 2011 . USENIX Association. A. Ghodsi, M. Zaharia, B. Hindman, A. Konwinski, S. Shenker, and I. Stoica. Dominant resource fairness: Fair allocation of multiple resource types. In Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation, NSDI'11, pages 323-- 336, Berkeley, CA, USA, 2011. USENIX Association."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2619239.2626334"},{"key":"e_1_2_1_10_1","first-page":"719","volume-title":"Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems-","volume":"2","author":"Gutman A.","year":"2012","unstructured":"A. Gutman and N. Nisan . Fair allocation without trade . In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems- Volume 2 , pages 719 -- 728 . International Foundation for Autonomous Agents and Multiagent Systems , 2012 . A. Gutman and N. Nisan. Fair allocation without trade. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems- Volume 2, pages 719--728. International Foundation for Autonomous Agents and Multiagent Systems, 2012."},{"key":"e_1_2_1_11_1","volume-title":"Asymptotic convergence of scheduling policies with respect to slowdown","author":"M.","year":"2002","unstructured":"M. Harchol-balter, K. Sigman , and A. Wierman . Asymptotic convergence of scheduling policies with respect to slowdown . October 2002 . M. Harchol-balter, K. Sigman, and A. Wierman. Asymptotic convergence of scheduling policies with respect to slowdown. October 2002."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1272996.1273005"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2012.6195481"},{"key":"e_1_2_1_14_1","first-page":"351","volume-title":"Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, AA- MAS '13","author":"Kash I.","year":"2013","unstructured":"I. Kash , A. D. Procaccia , and N. Shah . No agent left behind: Dynamic fair division of multiple resources . In Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, AA- MAS '13 , pages 351 -- 358 , Richland, SC , 2013 . International Foundation for Autonomous Agents and Multiagent Systems. I. Kash, A. D. Procaccia, and N. Shah. No agent left behind: Dynamic fair division of multiple resources. In Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, AA- MAS '13, pages 351--358, Richland, SC, 2013. 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