Open AccessEnhanced Entropy‐Based Resource Searching in Unstructured P2P Networks
Author(s) -
Gong Weihua,
Jin Rong,
Yang Lianghuai,
Huang Decai
Publication year - 2015
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2015.04.002
Subject(s) - computer science , scalability , adaptability , flooding (psychology) , distributed computing , routing (electronic design automation) , resource (disambiguation) , computer network , overlay network , tree (set theory) , database , world wide web , the internet , psychology , ecology , mathematical analysis , mathematics , psychotherapist , biology
How to find desired resources efficiently and accurately is one fundamental challenge of any unstructured P2P networks, which is mainly involved some difficulties in the P2P overlay topology, data representationin peers and routing mechanism. In this paper, weaddress the issue of resilient routing in unstructured P2Pnetworks. An efficient algorithm called Query routing tree(QRT) based on maximum mutual information is proposedto improve the performance of resource searching, whichhas tightly associated the resource contents of peers withthe logical links in P2P network that makes the query messagesforwarded more effectively in similar peers and canhit more target resources faster. Additionally, we presentan optimized routing scheme with the query conditionstaken into account, to obtain the optimal routing tree withthe minimal information gain from the candidate tree setso as to adapt to different query types more flexibly. Thesimulation results show the proposed QRT can reduce thesearch cost more effectively and maintain higher targetshit rate than existing typical algorithms such as Flooding,k‐RW and APS. Finally, our optimized scheme is alsoproved to conduct high searching performance with nicerself‐adaptability and scalability in unstructured P2P networks.