• DocumentCode
    618118
  • Title

    A pareto-based genetic algorithm for optimized assignment of VM requests on a cloud brokering environment

  • Author

    Kessaci, Yacine ; Melab, Nouredine ; Talbi, El-Ghazali

  • Author_Institution
    INRIA Lille, LIFL, Univ. Lille 1, Villeneuve d´Ascq, France
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    2496
  • Lastpage
    2503
  • Abstract
    In this paper, we deal with cloud brokering for the assignment optimization of VM requests in three-tier cloud infrastructures. We investigate the Pareto-based meta-heuristic approach to take into account multiple client and broker-centric optimization criteria. We propose a new multi-objective Genetic Algorithm (MOGA-CB ) that can be integrated in a cloud broker. Two objectives are considered in the optimization process: minimizing both the response time and the cost of the selected VM instances to satisfy the clients and to maximize the profit of the broker. The approach has been experimented using realistic data of different types of Amazon EC2 instances and their pricing history. The reported results show that MOGA-CB provides efficiently effective Pareto sets of solutions.
  • Keywords
    Pareto optimisation; cloud computing; genetic algorithms; minimisation; pricing; profitability; virtual machines; Amazon EC2 instances; MOGA-CB; Pareto sets; Pareto-based genetic algorithm; Pareto-based metaheuristic approach; VM request assignment optimization; broker-centric optimization criteria; cloud brokering environment; multiobjective genetic algorithm; optimization process; pricing history; three-tier cloud infrastructures; Computational modeling; Economics; Equations; Genetic algorithms; Quality of service; Scheduling; Time factors; VM instances; VM requests; client satisfaction; cloud brokering; cloud computing; genetic algorithm; multi-objective optimization; scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557869
  • Filename
    6557869