{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T17:05:59Z","timestamp":1761930359358,"version":"3.41.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Key Research Project of Zhejiang Province","award":["2022C01145"],"award-info":[{"award-number":["2022C01145"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U20A20173","62125206"],"award-info":[{"award-number":["U20A20173","62125206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Serv. Comput."],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1109\/tsc.2023.3303344","type":"journal-article","created":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T17:34:23Z","timestamp":1691516063000},"page":"1168-1180","source":"Crossref","is-referenced-by-count":3,"title":["Scheduling Multi-Server Jobs With Sublinear Regrets via Online Learning"],"prefix":"10.1109","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2850-6815","authenticated-orcid":false,"given":"Hailiang","family":"Zhao","sequence":"first","affiliation":[{"name":"Hainan Institute of Zhejiang University, Sanya, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5015-6095","authenticated-orcid":false,"given":"Shuiguang","family":"Deng","sequence":"additional","affiliation":[{"name":"Hainan Institute of Zhejiang University, Sanya, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1133-5722","authenticated-orcid":false,"given":"Zhengzhe","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Hangzhou City University, Hangzhou, China"}]},{"given":"Xueqiang","family":"Yan","sequence":"additional","affiliation":[{"name":"Huawei Technologies Company Ltd, Shanghai, China"}]},{"given":"Jianwei","family":"Yin","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6872-8821","authenticated-orcid":false,"given":"Schahram","family":"Dustdar","sequence":"additional","affiliation":[{"name":"Distributed Systems Group, Technische Universit&#x00E4;t Wien, Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3090-1059","authenticated-orcid":false,"given":"Albert Y.","family":"Zomaya","sequence":"additional","affiliation":[{"name":"School of Computer Science, University of Sydney, Sydney, NSW, Australia"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2806777.2806849"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00099"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3052895"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3447385"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2022.3215947"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2018.8486422"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3539606"},{"key":"ref8","first-page":"463","article-title":"A unified architecture for accelerating distributed DNN training in heterogeneous GPU\/CPU clusters","volume-title":"Proc. 14th USENIX Symp. Operating Syst. Des. Implementation","author":"Jiang"},{"key":"ref9","first-page":"559","article-title":"Alpa: Automating inter- and intra-operator parallelism for distributed deep learning","volume-title":"Proc. 16th USENIX Symp. Operating Syst. Des. Implementation","author":"Zheng"},{"key":"ref10","first-page":"673","article-title":"Whale: Efficient giant model training over heterogeneous GPUs","volume-title":"Proc. USENIX Annu. Tech. Conf.","author":"Jia"},{"key":"ref11","first-page":"41","article-title":"Managing large graphs on multi-cores with graph awareness","volume-title":"Proc. USENIX Annu. Tech. Conf.","author":"Prabhakaran"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3341302.3342080"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155445"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737465"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737612"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737370"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2018.8486340"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488916"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.15215\/aupress\/9781897425084.01"},{"key":"ref20","first-page":"323","article-title":"Dominant resource fairness: Fair allocation of multiple resource types","volume-title":"Proc. 8th USENIX Symp. Netw. Syst. Des. Implementation","author":"Ghodsi"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA.2018.00073"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3342195.3387547"},{"key":"ref23","first-page":"945","article-title":"MLaaS in the wild: Workload analysis and scheduling in large-scale heterogeneous GPU clusters","volume-title":"Proc. 19th USENIX Symp. Netw. Syst. Des. Implementation","author":"Weng"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/12.24272"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1186\/s13677-022-00377-4"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1561\/2200000018"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3392143"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10208-006-0237-y"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737446"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2020.2968424"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2021.3062269"},{"article-title":"A modern introduction to online learning","year":"2019","author":"Orabona","key":"ref32"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/2523616.2523633"},{"key":"ref35","first-page":"295","article-title":"Mesos: A platform for fine-grained resource sharing in the data center","volume-title":"Proc. 8th USENIX Symp. Netw. Syst. Des. Implementation","author":"Hindman"},{"year":"2022","key":"ref36","article-title":"Volcano"},{"key":"ref37","first-page":"1","article-title":"Pollux: Co-adaptive cluster scheduling for goodput-optimized deep learning","volume-title":"Proc. 15th USENIX Symp. Operating Syst. Des. Implementation","author":"Qiao"},{"key":"ref38","first-page":"481","article-title":"Heterogeneity-aware cluster scheduling policies for deep learning workloads","volume-title":"Proc. 14th USENIX Symp. Operating Syst. Des. Implementation","author":"Narayanan"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2018.2873373"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2018.00094"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/MobileCloud.2019.00018"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2019.2919553"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2019.2961905"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2019.2953806"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-47436-2_68"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488701"}],"container-title":["IEEE Transactions on Services Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4629386\/10554674\/10213224.pdf?arnumber=10213224","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T03:06:56Z","timestamp":1750129616000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10213224\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5]]},"references-count":45,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tsc.2023.3303344","relation":{},"ISSN":["1939-1374","2372-0204"],"issn-type":[{"type":"electronic","value":"1939-1374"},{"type":"electronic","value":"2372-0204"}],"subject":[],"published":{"date-parts":[[2024,5]]}}}