{"title":"混合电/光数据中心网络数据并行框架的作业调度","authors":"Zhuozhao Li, Haiying Shen","doi":"10.1145/3127479.3132694","DOIUrl":null,"url":null,"abstract":"In spite of many advantages of hybrid electrical/optical datacenter networks (Hybrid-DCN), current job schedulers for data-parallel frameworks are not suitable for Hybrid-DCN, since the schedulers do not aggregate data traffic to facilitate using optical circuit switch (OCS). We propose SchedOCS, a job scheduler for data-parallel frameworks in Hybrid-DCN that aims to take full advantage of the OCS to improve the job performance.","PeriodicalId":20679,"journal":{"name":"Proceedings of the 2017 Symposium on Cloud Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Job scheduling for data-parallel frameworks with hybrid electrical/optical datacenter networks\",\"authors\":\"Zhuozhao Li, Haiying Shen\",\"doi\":\"10.1145/3127479.3132694\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In spite of many advantages of hybrid electrical/optical datacenter networks (Hybrid-DCN), current job schedulers for data-parallel frameworks are not suitable for Hybrid-DCN, since the schedulers do not aggregate data traffic to facilitate using optical circuit switch (OCS). We propose SchedOCS, a job scheduler for data-parallel frameworks in Hybrid-DCN that aims to take full advantage of the OCS to improve the job performance.\",\"PeriodicalId\":20679,\"journal\":{\"name\":\"Proceedings of the 2017 Symposium on Cloud Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 Symposium on Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3127479.3132694\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 Symposium on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3127479.3132694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Job scheduling for data-parallel frameworks with hybrid electrical/optical datacenter networks
In spite of many advantages of hybrid electrical/optical datacenter networks (Hybrid-DCN), current job schedulers for data-parallel frameworks are not suitable for Hybrid-DCN, since the schedulers do not aggregate data traffic to facilitate using optical circuit switch (OCS). We propose SchedOCS, a job scheduler for data-parallel frameworks in Hybrid-DCN that aims to take full advantage of the OCS to improve the job performance.
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