{"title":"B-MAPS:异构云系统的自适应资源调度框架","authors":"Joal Wood, B. Romoser, I. Zecena, Ziliang Zong","doi":"10.1145/2494621.2494640","DOIUrl":null,"url":null,"abstract":"Future cloud systems will become increasingly complicated and highly heterogeneous. It is paramount to develop new techniques that can achieve high performance and low energy consumption in future cloud systems. However, this is not a trivial task because the dynamic nature of system status and user workloads requires that the system must be able to trade off performance and energy efficiency at real time. In this paper, we propose B-MAPS, a self-adaptive resource scheduling framework, which has the potential to improve the performance and energy-efficiency of multi-core or many-core based heterogeneous cloud systems.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"B-MAPS: a self-adaptive resource scheduling framework for heterogeneous cloud systems\",\"authors\":\"Joal Wood, B. Romoser, I. Zecena, Ziliang Zong\",\"doi\":\"10.1145/2494621.2494640\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Future cloud systems will become increasingly complicated and highly heterogeneous. It is paramount to develop new techniques that can achieve high performance and low energy consumption in future cloud systems. However, this is not a trivial task because the dynamic nature of system status and user workloads requires that the system must be able to trade off performance and energy efficiency at real time. In this paper, we propose B-MAPS, a self-adaptive resource scheduling framework, which has the potential to improve the performance and energy-efficiency of multi-core or many-core based heterogeneous cloud systems.\",\"PeriodicalId\":190559,\"journal\":{\"name\":\"ACM Cloud and Autonomic Computing Conference\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Cloud and Autonomic Computing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2494621.2494640\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Cloud and Autonomic Computing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2494621.2494640","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
B-MAPS: a self-adaptive resource scheduling framework for heterogeneous cloud systems
Future cloud systems will become increasingly complicated and highly heterogeneous. It is paramount to develop new techniques that can achieve high performance and low energy consumption in future cloud systems. However, this is not a trivial task because the dynamic nature of system status and user workloads requires that the system must be able to trade off performance and energy efficiency at real time. In this paper, we propose B-MAPS, a self-adaptive resource scheduling framework, which has the potential to improve the performance and energy-efficiency of multi-core or many-core based heterogeneous cloud systems.