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
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