A simple cluster-scaling policy for MapReduce clouds

Sheng Wei Huang, Ce Kuen Shieh, Syue Ru Lyu, Tzu Chi Huang, Chien Sheng Chen, Ping Fan Ho, Ming Fong Tsai

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

Abstract

Due to the rise of cloud computing, many cloud services have been developed. Google proposed a programming model called MapReduce for processing large amounts of data. After YAHOO! proposed Hadoop, many companies and enterprises have started using this programming model to establish their own cluster for handling large amounts of data.

Original languageEnglish
Title of host publication2013 International Symposium on Wireless and Pervasive Computing, ISWPC 2013
DOIs
StatePublished - 2013
Event2013 International Symposium on Wireless and Pervasive Computing, ISWPC 2013 - Taipei, Taiwan
Duration: 20 Nov 201322 Nov 2013

Publication series

Name2013 International Symposium on Wireless and Pervasive Computing, ISWPC 2013

Conference

Conference2013 International Symposium on Wireless and Pervasive Computing, ISWPC 2013
CountryTaiwan
CityTaipei
Period20/11/1322/11/13

Keywords

  • Cloud Computing
  • Cluster scaling
  • MapReduce
  • Power saving

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  • Cite this

    Huang, S. W., Shieh, C. K., Lyu, S. R., Huang, T. C., Chen, C. S., Ho, P. F., & Tsai, M. F. (2013). A simple cluster-scaling policy for MapReduce clouds. In 2013 International Symposium on Wireless and Pervasive Computing, ISWPC 2013 [6707441] (2013 International Symposium on Wireless and Pervasive Computing, ISWPC 2013). https://doi.org/10.1109/ISWPC.2013.6707441