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