Computer Science ›› 2019, Vol. 46 ›› Issue (11A): 354-358, 386.

• Network & Communication • Previous Articles     Next Articles

Cost-driven Workflow Data Placement Method in Hybrid Cloud Environment

HUANG Yin-hao1,2, MA Yun3, LIN Bing2,4, YU Zhi-yong1,2, CHEN Xing1,2   

  1. (College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350116,China)1;
    (Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing,Fuzhou 350116,China)2;
    (School of Software,Tsinghua University,Beijing 100084,China)3;
    (College of Physics and Energy,Fujian Normal University,Fuzhou 350117,China)4
  • Online:2019-11-10 Published:2019-11-20

Abstract: Scientific workflow execution in hybrid cloud will generate a lot of transmission across data centers,resulting in large quantities propagation delay time and cost.In order to make a reasonable data placement of scientific workflow in hybrid cloud environment,it takes into account the advantages of public cloud and private cloud,and optimizes the cost of data placement.A data placement strategy based on genetic algorithm particle swarm optimization (GAPSO) was proposed,which considers the different characteristics between public cloud data centers and private cloud data centers such as capacity and storage cost as well as the influence of propagation delay time constraint on transmission costs and combining the advantages of genetic algorithm and particle swarm optimization algorithm,and data placement stra-tegy for scientific workflows was generated.The experimental results show that the data placement strategy based on GAPSO can effectively reduce the cost of data placement of scientific workflow in hybrid cloud.

Key words: Hybrid cloud, Data placement, Propagation delay time constraint, Cost-driven

CLC Number: 

  • TP338
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