• DocumentCode
    2183046
  • Title

    PACO: A Period ACO Based Scheduling Algorithm in Cloud Computing

  • Author

    Weifeng Sun ; Ning Zhang ; Haotian Wang ; Wenjuan Yin ; Tie Qiu

  • Author_Institution
    Sch. of Software Technol., Dalian Univ. of Technol., Dalian, China
  • fYear
    2013
  • fDate
    16-19 Dec. 2013
  • Firstpage
    482
  • Lastpage
    486
  • Abstract
    Tasks scheduling problem in cloud computing is NP-hard, and it is difficult to attain an optimal solution, so we can use intelligent optimization algorithms to approximate the optimal solution, such as ant colony optimization algorithm. In order to solve the task scheduling problem in cloud computing, a period ACO_based scheduling algorithm (PACO) has been proposed in this paper. PACO uses ant colony optimization algorithm in cloud computing, with the first proposed scheduling period strategy and the improvement of pheromone intensity update strategy. The experiments results show that, PACO has a good performance both in makespan and load balance of the whole cloud cluster.
  • Keywords
    ant colony optimisation; cloud computing; computational complexity; scheduling; NP-hard problem; PACO; ant colony optimization algorithm; cloud cluster; cloud computing; intelligent optimization algorithms; period ACO based scheduling algorithm; tasks scheduling problem; Algorithm design and analysis; Cloud computing; Clustering algorithms; Heuristic algorithms; Scheduling; Scheduling algorithms; ant colony algorithm; cloud computing; scheduling period; task scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
  • Conference_Location
    Fuzhou
  • Print_ISBN
    978-1-4799-2829-3
  • Type

    conf

  • DOI
    10.1109/CLOUDCOM-ASIA.2013.85
  • Filename
    6821036