Speed-based load balancer for scheduling reduce tasks to process intermediate data of MapReduce applications on cloud computing

Tzu Chi Huang, Kuo Chih Chu, Ce Kuen Shieh, Ming Fong Tsai

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

MapReduce is a programming model used to develop applications on cloud computing. However, MapReduce strongly relies on the runtime system to handle issues of task managements in order to get a better performance. While most research works focus on scheduling Map tasks to improve performances, MapReduce is identified by this paper to have the potential for performance improvements through the Speed-based Load Balancer (SLB) for scheduling Reduce tasks. According to observations on experiments of Inverted Index, Radix Sort and Word Count, MapReduce can use SLB to outperform the native scheduler used by Hadoop in the runtime system.

原文English
主出版物標題Proceedings of the ASE BigData and SocialInformatics 2015, ASE BD and SI 2015
發行者Association for Computing Machinery
ISBN(電子)9781450337359
DOIs
出版狀態Published - 2015 十月 7
事件ASE BigData and SocialInformatics, ASE BD and SI 2015 - Kaohsiung, Taiwan
持續時間: 2015 十月 72015 十月 9

出版系列

名字ACM International Conference Proceeding Series
07-09-Ocobert-2015

Other

OtherASE BigData and SocialInformatics, ASE BD and SI 2015
國家Taiwan
城市Kaohsiung
期間15-10-0715-10-09

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • 引用此

    Huang, T. C., Chu, K. C., Shieh, C. K., & Tsai, M. F. (2015). Speed-based load balancer for scheduling reduce tasks to process intermediate data of MapReduce applications on cloud computing. 於 Proceedings of the ASE BigData and SocialInformatics 2015, ASE BD and SI 2015 [a49] (ACM International Conference Proceeding Series; 卷 07-09-Ocobert-2015). Association for Computing Machinery. https://doi.org/10.1145/2818869.2818880