• DocumentCode
    1638608
  • Title

    Dynamic search initialisation strategies for multi-objective optimisation in peer-to-peer networks

  • Author

    Scriven, Ian ; Lewis, Andrew ; Mostaghim, Sanaz

  • Author_Institution
    Sch. of Eng., Griffith Univ., Brisbane, QLD
  • fYear
    2009
  • Firstpage
    1515
  • Lastpage
    1522
  • Abstract
    Peer-to-peer based distributed computing environments can be expected to be dynamic to greater of lesser degree. While node losses will not usually lead to catastrophic failure of a population-based optimisation algorithm, such as particle swarm optimisation, performance will be degraded unless the lost computational power is replaced. When resources are replaced, one must consider how to utilise newly available nodes as well as the loss of existing nodes. In order to take advantage of newly available nodes, new particles must be generated to populate them. This paper proposes two methods of generating new particles during algorithm execution and compares the performance of each approach, then investigates a hybridised approach incorporating both mechanisms.
  • Keywords
    particle swarm optimisation; peer-to-peer computing; search problems; distributed computing environments; dynamic search initialisation strategies; multiobjective optimisation; particle swarm optimisation; peer-to-peer networks; population-based optimisation algorithm; Concurrent computing; Degradation; Design optimization; Distributed computing; Grid computing; Hybrid power systems; Optimization methods; Particle swarm optimization; Peer to peer computing; Performance loss;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983122
  • Filename
    4983122