Power provisioning for a warehouse-sized computer
Proceedings of the 34th annual international symposium on Computer architecture
Multi-mode energy management for multi-tier server clusters
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
Internet-scale service infrastructure efficiency
Proceedings of the 36th annual international symposium on Computer architecture
Power management of online data-intensive services
Proceedings of the 38th annual international symposium on Computer architecture
Taming power peaks in mapreduce clusters
Proceedings of the ACM SIGCOMM 2011 conference
Energy efficiency for large-scale MapReduce workloads with significant interactive analysis
Proceedings of the 7th ACM european conference on Computer Systems
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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. Wc 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.