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
Link To Document :
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