Name
Abstract | ||
|---|---|---|
Along with the surging service demands in the cloud, power provision infrastructure of Internet Data Centers (IDCs) has brought dramatically increasing capital cost. To enlarge the size of IDCs with lowest cost, power management of computing facilities has attracted many attentions in recent. A large portion of applications running on data centers are data-intensive and throughput-preferredMapReduce is one of them enjoying widely deployment. However the critical power peak problem in MapReduce clusters, which actually limits the cluster's size, has been overlooked. We study the power peak problem in MapReduce system and investigate the reason causing it. We design an adaptive approach to regulate power peaks. Evaluation result shows that our proposed method can effectively smooth the power consumption curve by reducing the peak value for 20% with little overhead in performance, and in turn extending the maximum size of the cluster with 25% under the same power budget. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2349896.2349899 | ApSys |
Keywords | Field | DocType |
power management,power provision infrastructure,peak value,power peak problem,mapreduce cluster,critical power peak problem,power peak,power consumption curve,maximum size,power budget,fault tolerance,data center | Power budget,Power management,Cluster (physics),Capital cost,Software deployment,Computer science,Fault tolerance,The Internet,Distributed computing,Cloud computing | Conference |
Citations | PageRank | References |
1 | 0.35 | 8 |
Authors | ||
4 | ||