{"title":"Power Management in Heterogeneous Multi-tier Web Clusters","authors":"Peijian Wang, Yongwei Qi, Xue Liu, Ying Chen, Xiao Zhong","doi":"10.1109/ICPP.2010.46","DOIUrl":null,"url":null,"abstract":"Complex web applications are usually served by multi-tier web clusters. With the growing cost of energy, the importance of reducing power consumption in server systems is now well-known and has become a major research topic. However, most of previous works focused solely on homogeneous clusters. This paper addresses the challenge of power management in Heterogeneous Multi-tier Web Clusters. We apply Generalized Benders Decomposition (GBD) to decompose the global optimization problem into small sub-problems. This algorithm achieves the optimal solution in an iterative fashion. The simulation results show that our algorithm achieve more energy conservation than the previous works.","PeriodicalId":180554,"journal":{"name":"2010 39th International Conference on Parallel Processing","volume":"1999 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 39th International Conference on Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPP.2010.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Complex web applications are usually served by multi-tier web clusters. With the growing cost of energy, the importance of reducing power consumption in server systems is now well-known and has become a major research topic. However, most of previous works focused solely on homogeneous clusters. This paper addresses the challenge of power management in Heterogeneous Multi-tier Web Clusters. We apply Generalized Benders Decomposition (GBD) to decompose the global optimization problem into small sub-problems. This algorithm achieves the optimal solution in an iterative fashion. The simulation results show that our algorithm achieve more energy conservation than the previous works.