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
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;
Conference_Titel :
Computers and Communications, 2005. ISCC 2005. Proceedings. 10th IEEE Symposium on
Print_ISBN :
0-7695-2373-0
DOI :
10.1109/ISCC.2005.89