Title :
Enhanced Energy-Efficient Scheduling for Parallel Applications in Cloud
Author :
Huang, Qingjia ; Su, Sen ; Li, Jian ; Xu, Peng ; Shuang, Kai ; Huang, Xiao
Author_Institution :
State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
Energy consumption has become a major concern to the widespread deployment of cloud data centers. The growing importance for parallel applications in the cloud introduces significant challenges in reducing the power consumption drawn by the hosted servers. In this paper, we propose an enhanced energy-efficient scheduling (EES) algorithm to reduce energy consumption while meeting the performance-based service level agreement (SLA). Since slacking non-critical jobs can achieve significant power saving, we exploit the slack room and allocate them in a global manner in our schedule. Using random generated and real-life application workflows, our results demonstrate that EES is able to reduce considerable energy consumption while still meeting SLA.
Keywords :
cloud computing; computer centres; parallel processing; power aware computing; scheduling; EES; SLA; cloud data centers; energy consumption; energy-efficient scheduling algorithm; parallel applications; performance-based service level agreement; power consumption reduction; random generated application workflows; real-life application workflows; slack room; Clustering algorithms; Energy consumption; Heuristic algorithms; Job shop scheduling; Processor scheduling; Schedules; Cloud Data Center; Directed Acyclic Graph; Energy-efficient Scheduling; List Scheduling; Parallel Applications; Performance Guarantee;
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4673-1395-7
DOI :
10.1109/CCGrid.2012.49