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Scalable Search based on Fuzzy Clustering for Interest-based P2P Networks
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  • Scalable Search based on Fuzzy Clustering for Interest-based P2P Networks
  • Scalable Search based on Fuzzy Clustering for Interest-based P2P Networks
저자명
Mateo. Romeo Mark A.,Lee. Jae-Wan
간행물명
KSII Transactions on internet and information systems : TIIS
권/호정보
2011년|5권 1호|pp.157-176 (20 pages)
발행정보
한국인터넷정보학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

An interest-based P2P constructs the peer connections based on similarities for efficient search of resources. A clustering technique using peer similarities as data is an effective approach to group the most relevant peers. However, the separation of groups produced from clustering lowers the scalability of a P2P network. Moreover, the interest-based approach is only concerned with user-level grouping where topology-awareness on the physical network is not considered. This paper proposes an efficient scalable search for the interest-based P2P system. A scalable multi-ring (SMR) based on fuzzy clustering handles the grouping of relevant peers and the proposed scalable search utilizes the SMR for scalability of peer queries. In forming the multi-ring, a minimized route function is used to determine the shortest route to connect peers on the physical network. Performance evaluation showed that the SMR acquired an accurate peer grouping and improved the connectivity rate of the P2P network. Also, the proposed scalable search was efficient in finding more replicated files throughout the peer network compared to other traditional P2P approaches.