Scalable Grouping Based on Neuro-Fuzzy Clustering for P2P Networks

Authors:
Romeo Mark Mateo;Hyunho Yang;Jaewan Lee
Affiliations:
School of Electronic and Information Engineering, Kunsan National University, Chonbuk, South Korea 573-701;School of Electronic and Information Engineering, Kunsan National University, Chonbuk, South Korea 573-701;School of Electronic and Information Engineering, Kunsan National University, Chonbuk, South Korea 573-701
Venue:
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Year:
2009

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Abstract

In this paper, we present a scalable grouping based on the proposed neuro-fuzzy clustering (NFC) which is a combination of fuzzy clustering and neuro-fuzzy classification for P2P networks. Fuzzy clustering is used to construct the classifier structure for the grouping technique and neuro-fuzzy algorithm is used to adjust the fuzzy system in creating the accurate classifier. After the adjustment, each peer is processed in multi-ring algorithm using the fuzzy membership function of NFC. The scalable peer grouping contributes on load distribution by forwarding incoming request to the least loaded peer. Performance result showed that the proposed scalable peer grouping classifies more peers in a group for availability of resources and accurately classifies peer group.