Distributed control framework for mapreduce cloud on cloud computing

Tzu Chi Huang, Kuo Chih Chu, Guo Hao Huang, Yan Chen Shen, Ce Kuen Shieh

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

A MapReduce cloud becomes a key to the success of cloud computing today. However, a MapReduce cloud uses a single Master node as the brain to manage tasks distributed over Slave nodes for controlling the entire progress of the application execution. Accordingly, a MapReduce cloud easily overloads the Master node with reports sent from Slave nodes at run time to harm performance. Besides, a MapReduce cloud makes the Master node a single failure point to suspend the application execution when the Master node cannot work. A MapReduce cloud can use the Distributed Control Framework (DCF) proposed in this paper to improve both performance and fault tolerance, because DCF shifts most works of a Master node to a DCF Master Agent coexisting in each Slave node and allows Slave nodes to join or leave a cloud at run time without interrupting the application execution. According to observations on experiments with various applications in this paper, a MapReduce cloud can use DCF to have better performance and fault tolerance in comparison to a native MapReduce cloud.

原文English
主出版物標題IEEE/IFIP Network Operations and Management Symposium
主出版物子標題Cognitive Management in a Cyber World, NOMS 2018
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1-4
頁數4
ISBN(電子)9781538634165
DOIs
出版狀態Published - 2018 7月 6
事件2018 IEEE/IFIP Network Operations and Management Symposium, NOMS 2018 - Taipei, Taiwan
持續時間: 2018 4月 232018 4月 27

出版系列

名字IEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018

Other

Other2018 IEEE/IFIP Network Operations and Management Symposium, NOMS 2018
國家/地區Taiwan
城市Taipei
期間18-04-2318-04-27

All Science Journal Classification (ASJC) codes

  • 安全、風險、可靠性和品質
  • 電腦網路與通信
  • 資訊系統與管理
  • 控制和優化

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