Exploiting spatio-temporal tradeoffs for energy-aware mapreduce in the cloud

Michael Cardosa, Aameek Singh, Himabindu Pucha, Abhishek Chandra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations

Abstract

MapReduce is a distributed computing paradigm widely used for building large-scale data processing applications. When used in cloud environments, MapReduce clusters are dynamically created using virtual machines (VMs) and managed by the cloud provider. In this paper, we study the energy efficiency problem for such MapReduce clusters in private cloud environments, that are characterized by repeated, batch execution of jobs. We describe a unique spatio-temporal tradeoff that includes efficient spatial fitting of VMs on servers to achieve high utilization of machine resources, as well as balanced temporal fitting of servers with VMs having similar runtimes to ensure a server runs at a high utilization throughout its uptime. We propose VM placement algorithms that explicitly incorporate these tradeoffs. Our algorithms achieve energy savings over existing placement techniques, and an additional optimization technique further achieves savings while simultaneously improving job performance.

Original languageEnglish (US)
Title of host publicationProceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011
Pages251-258
Number of pages8
DOIs
StatePublished - Sep 29 2011
Event2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011 - Washington, DC, United States
Duration: Jul 4 2011Jul 9 2011

Publication series

NameProceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011

Other

Other2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011
CountryUnited States
CityWashington, DC
Period7/4/117/9/11

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    Cardosa, M., Singh, A., Pucha, H., & Chandra, A. (2011). Exploiting spatio-temporal tradeoffs for energy-aware mapreduce in the cloud. In Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011 (pp. 251-258). [6008717] (Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011). https://doi.org/10.1109/CLOUD.2011.68