DocumentCode :
1665113
Title :
iXChange - a self-organising super peer network model
Author :
Johnstone, S. ; Sage, P. ; Milligan, P.
Author_Institution :
Sch. of Comput. Sci., Queen´´s Univ., Belfast, UK
fYear :
2005
Firstpage :
164
Lastpage :
169
Abstract :
A self-organising, peer-to-peer, network model, iXChange, is presented. Peers share information, such as usage history and centres of interest, to self organise into semantically clustered groups and intelligently elect super peers using a neural network. Super peers can efficiently route queries based on a small world model and demonstrate a strong self organisational capability using ontology based interest representations. Preliminary results show that the neural network super peer election architecture can be trained in an acceptably low amount of time resulting in successful autonomous election of efficient and reliable super peers.
Keywords :
neural nets; ontologies (artificial intelligence); peer-to-peer computing; iXChange; neural network; ontology representation; peer election architecture; self-organising super peer network model; small world model; Bandwidth; Collaboration; Computer science; Information retrieval; Large-scale systems; Length measurement; Peer to peer computing; Query processing; Routing; Size measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers and Communications, 2005. ISCC 2005. Proceedings. 10th IEEE Symposium on
ISSN :
1530-1346
Print_ISBN :
0-7695-2373-0
Type :
conf
DOI :
10.1109/ISCC.2005.89
Filename :
1493723
Link To Document :
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