{"title":"MEC-IDC:分布式互联网数据中心的联合负载均衡与功率控制","authors":"Lei Rao, Xue Liu, M. Ilić, Jie Liu","doi":"10.1145/1795194.1795220","DOIUrl":null,"url":null,"abstract":"Internet Data Center (IDC) supports the reliable operations of many important Internet on-line services. As the demand on Internet services and cloud computing keep increasing in recent years, the power usage associated with IDC operations has been uprising significantly. The cyber and physical aspects of IDCs interact with each other, and brings unprecedented challenges in power management. While most existing research focuses on reducing power consumptions of IDCs, this paper studies the problem of minimizing the total electricity cost geared to quality of service constraint as well as the location diversity and time diversity of electricity price under multiple electricity markets. We jointly consider both the cyber and physical management capabilities of IDCs, and exploit both the center-level load balancing, and the server-level power control in a unified scheme. We model the problem as a constrained mixed integer programming based on Generalized Benders Decomposition (GBD) technique. Extensive evaluations based on real-life electricity price data for multiple IDC locations demonstrates the effectiveness of our scheme.","PeriodicalId":6619,"journal":{"name":"2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)","volume":"17 5","pages":"188-197"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":"{\"title\":\"MEC-IDC: joint load balancing and power control for distributed Internet Data Centers\",\"authors\":\"Lei Rao, Xue Liu, M. Ilić, Jie Liu\",\"doi\":\"10.1145/1795194.1795220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Internet Data Center (IDC) supports the reliable operations of many important Internet on-line services. As the demand on Internet services and cloud computing keep increasing in recent years, the power usage associated with IDC operations has been uprising significantly. The cyber and physical aspects of IDCs interact with each other, and brings unprecedented challenges in power management. While most existing research focuses on reducing power consumptions of IDCs, this paper studies the problem of minimizing the total electricity cost geared to quality of service constraint as well as the location diversity and time diversity of electricity price under multiple electricity markets. We jointly consider both the cyber and physical management capabilities of IDCs, and exploit both the center-level load balancing, and the server-level power control in a unified scheme. We model the problem as a constrained mixed integer programming based on Generalized Benders Decomposition (GBD) technique. Extensive evaluations based on real-life electricity price data for multiple IDC locations demonstrates the effectiveness of our scheme.\",\"PeriodicalId\":6619,\"journal\":{\"name\":\"2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)\",\"volume\":\"17 5\",\"pages\":\"188-197\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"46\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1795194.1795220\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1795194.1795220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 46
摘要
互联网数据中心(Internet Data Center, IDC)支持着许多重要的互联网在线业务的可靠运行。近年来,随着互联网服务和云计算需求的不断增长,与IDC运营相关的用电量大幅上升。idc的网络和物理方面相互影响,给电源管理带来了前所未有的挑战。现有的研究大多集中在降低idc的电力消耗上,而本文研究的是在多个电力市场条件下,考虑服务质量约束以及电价的地点多样性和时间多样性,使总电力成本最小化的问题。我们综合考虑idc的网络和物理管理能力,并在统一的方案中利用中心级负载均衡和服务器级功率控制。基于广义Benders分解(GBD)技术,将该问题建模为约束混合整数规划问题。基于多个IDC地点的实际电价数据的广泛评估证明了我们方案的有效性。
MEC-IDC: joint load balancing and power control for distributed Internet Data Centers
Internet Data Center (IDC) supports the reliable operations of many important Internet on-line services. As the demand on Internet services and cloud computing keep increasing in recent years, the power usage associated with IDC operations has been uprising significantly. The cyber and physical aspects of IDCs interact with each other, and brings unprecedented challenges in power management. While most existing research focuses on reducing power consumptions of IDCs, this paper studies the problem of minimizing the total electricity cost geared to quality of service constraint as well as the location diversity and time diversity of electricity price under multiple electricity markets. We jointly consider both the cyber and physical management capabilities of IDCs, and exploit both the center-level load balancing, and the server-level power control in a unified scheme. We model the problem as a constrained mixed integer programming based on Generalized Benders Decomposition (GBD) technique. Extensive evaluations based on real-life electricity price data for multiple IDC locations demonstrates the effectiveness of our scheme.