• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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A survey of task management techniques
 for big data stream computing

LIANG Yi1,HOU Ying1,CHEN Cheng1,JIN Yi2   

  1. (1.College of Computer Science,Beijing University of Technology,Beijing 100124;
    2.Beijing Computing Center,Beijing 100094,China)
  • Received:2016-09-08 Revised:2016-11-02 Online:2017-02-25 Published:2017-02-25

Abstract:

Stream computing is an important part of  big data computing, which has become a hot topic in big data research. Task management is one of the essential features of stream computing, and is responsible for resource scheduling and lifecycle management of stream computing tasks. Current researches focus on application requirements, architecture and overall technology of stream computing, and they are lack of dedicated investigation and analysis of task management techniques. Firstly, we present a general abstract function model of task management for stream computing systems. Secondly, we classify and analyze the key techniques for task management based on this model. Finally, we investigate their applications in  current stream processing systems, and the integration and optimization of above techniques.

Key words: big data stream computing, task management, abstract function model, resource allocation, data distribution, fault tolerance