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Multi-objective Optimization for Data Placement Strategy in Cloud Computing

  • Lizheng Guo
  • Zongyao He
  • Shuguang Zhao
  • Na Zhang
  • Junhao Wang
  • Changyun Jiang
Part of the Communications in Computer and Information Science book series (CCIS, volume 308)

Abstract

In cloud computing, the data of processing and the data of transfering is charged at for the service of the provider. So, it is important to reduce the cost and to improve the performance for the consumer of the cloud computing. At present, the existing optimization algorithms only focus on one aspect , such as reducing the move of data, the processing time, the transferring time, the processing cost or the transferring cost. This paper makes a model for the multi-objective data placement and uses a particle swarm optimization algorithm to optimize the time and cost in cloud computing. The mode applied processors interaction graph to map the data of the task and the data center. The simulation experimental result manifests that the proposed method is more effective in time and cost.

Keywords

Cloud Computing Particle Swarm Optimization Multi-Objective Optimization Data Placement 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Lizheng Guo
    • 1
    • 2
  • Zongyao He
    • 1
  • Shuguang Zhao
    • 2
  • Na Zhang
    • 2
  • Junhao Wang
    • 2
  • Changyun Jiang
    • 2
  1. 1.Department of Computer Science and EngineeringHenan University of Urban ConstructioinPingdingshanChina
  2. 2.College of Information Science and TechnologyDonghua UniversityShanghaiChina

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