{"title":"最小化具有动态流量的互联网规模数据中心的能源成本","authors":"Dan Xu, Xin Liu, Bin Fan","doi":"10.1109/IWQOS.2011.5931322","DOIUrl":null,"url":null,"abstract":"In this paper, our goal is to achieve an optimal tradeoff between energy efficiency and service performance over a set of distributed IDCs with dynamic demand. In particular, we consider the outage probability as the QoS metric, where outage is defined as service demand exceeding the capacity of an IDC. Our goal is thus to minimize total energy cost over all IDCs, subject to the outage probability constraint. We achieve the goal by dynamically adjusting server capacity and performing load shifting in different time scales. We propose three different load-shifting and joint capacity allocation schemes with different complexity and performance. Our schemes leverage both stochastic multiplexing gain and electricity-price diversity.","PeriodicalId":127279,"journal":{"name":"2011 IEEE Nineteenth IEEE International Workshop on Quality of Service","volume":"353 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Minimizing energy cost for Internet-scale datacenters with dynamic traffic\",\"authors\":\"Dan Xu, Xin Liu, Bin Fan\",\"doi\":\"10.1109/IWQOS.2011.5931322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, our goal is to achieve an optimal tradeoff between energy efficiency and service performance over a set of distributed IDCs with dynamic demand. In particular, we consider the outage probability as the QoS metric, where outage is defined as service demand exceeding the capacity of an IDC. Our goal is thus to minimize total energy cost over all IDCs, subject to the outage probability constraint. We achieve the goal by dynamically adjusting server capacity and performing load shifting in different time scales. We propose three different load-shifting and joint capacity allocation schemes with different complexity and performance. Our schemes leverage both stochastic multiplexing gain and electricity-price diversity.\",\"PeriodicalId\":127279,\"journal\":{\"name\":\"2011 IEEE Nineteenth IEEE International Workshop on Quality of Service\",\"volume\":\"353 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE Nineteenth IEEE International Workshop on Quality of Service\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWQOS.2011.5931322\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Nineteenth IEEE International Workshop on Quality of Service","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQOS.2011.5931322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Minimizing energy cost for Internet-scale datacenters with dynamic traffic
In this paper, our goal is to achieve an optimal tradeoff between energy efficiency and service performance over a set of distributed IDCs with dynamic demand. In particular, we consider the outage probability as the QoS metric, where outage is defined as service demand exceeding the capacity of an IDC. Our goal is thus to minimize total energy cost over all IDCs, subject to the outage probability constraint. We achieve the goal by dynamically adjusting server capacity and performing load shifting in different time scales. We propose three different load-shifting and joint capacity allocation schemes with different complexity and performance. Our schemes leverage both stochastic multiplexing gain and electricity-price diversity.