Gossip-Based Resource Location Strategy in Interest Community for P2P Networks

HE Ming; ZHANG Yujie; MENG Xiangwu

doi:10.1049/cje.2015.04.008

Volume 24 Issue 2

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HE Ming, ZHANG Yujie, MENG Xiangwu, “Gossip-Based Resource Location Strategy in Interest Community for P2P Networks,” Chinese Journal of Electronics, vol. 24, no. 2, pp. 272-280, 2015, doi: 10.1049/cje.2015.04.008

Citation:

HE Ming, ZHANG Yujie, MENG Xiangwu, “Gossip-Based Resource Location Strategy in Interest Community for P2P Networks,” Chinese Journal of Electronics, vol. 24, no. 2, pp. 272-280, 2015, doi: 10.1049/cje.2015.04.008

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Gossip-Based Resource Location Strategy in Interest Community for P2P Networks

doi: 10.1049/cje.2015.04.008

1.
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2.
Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing 100876, China

Funds: This work is supported by the Program of the Co-construction with Beijing Municipal Commission of Education and the National Natural Science Foundation of China (No.61001118).

Publish Date: 2015-04-10

Abstract

Abstract

Resource location strategy has become very popular for mass data distribution in complex and dynamic network. Searching for the objects is a fundamental problem to unstructured Peer to peer (P2P) networks. In this paper, we propose a resource location strategy for user requirements, which employs the collaborative exchange of information between peers to construct interest communities. This strategy can gather similar peers and disseminate useful information among them. Furthermore, we design an algorithm in unstructured P2P systems named Appropriate degree gossip search algorithm (ADGSA). Using this search algorithm, the performance including search success ratio, recall rate and search response time has been improved dramatically. An efficient resource location system with a fast organization of users cluster based on their requirements can be provided, preventing the creation of unliked communities. The simulation results show that our strategy has better search efficiency, short response time and high recall ratio.
- Unstructured P2P network,
- Resource location,
- Interest community,
- Gossip-based search,
- Flooding

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References(23)

References

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