• DocumentCode
    694395
  • Title

    Research on cloud computing schedule based on improved hybrid PSO

  • Author

    Yang Xiaoguang ; Chen Tingbin ; Zhang Qisong

  • Author_Institution
    Inf. Technol. & Bus. Manage., Dalian Neusoft Univ. of Inf., Dalian, China
  • fYear
    2013
  • fDate
    12-13 Oct. 2013
  • Firstpage
    388
  • Lastpage
    391
  • Abstract
    In the cloud computing environment, one of the hot spot of researches in cloud computing is how to accomplish the service request in numerous running tasks. This paper puts forward an improved hybrid particle swarm optimization, making the particle swarm algorithm as the main level algorithm and the improved ant colony algorithm as the secondary level algorithm. The algorithm uses the main level algorithm to generate the initial pheromone distribution and utilizes the secondary algorithm that max-min ant colony algorithm to obtain the best solution. Finally, the availability and advantage of the proposed algorithm can be tested through the simulation experiment.
  • Keywords
    ant colony optimisation; cloud computing; minimax techniques; particle swarm optimisation; scheduling; cloud computing environment; cloud computing schedule; hybrid PSO; hybrid particle swarm optimization; max-min ant colony algorithm; particle swarm algorithm; pheromone distribution; secondary algorithm; secondary level algorithm; Algorithm design and analysis; Cloud computing; Information technology; Optimization; Particle swarm optimization; Processor scheduling; Scheduling; cloud computing; improved PSO algorithm; task scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
  • Conference_Location
    Dalian
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2013.6967136
  • Filename
    6967136