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British Journal of Mathematics & Computer Science, ISSN: 2231-0851,Vol.: 5, Issue.: 4

Original-research-article

Similarity-Based Content Retrieval in Self-Organizing Peer-to-Peer Networks

 

Takuya Yamaguchi1, Andrii Zhygmanovskyi1, Noriko Matsumoto1 and Norihiko Yoshida1

1Graduate School of Science and Engineering, University in Saitama, Japan.

Article Information
Editor(s):
(1) Xiaodi Li, School of Mathematical Sciences, Shandong Normal University Ji’nan, 250014, Shandong, P. R. China.
Reviewers:
(1) Tzvetalin S. Vassilev, Department of Computer Science and Mathematics, Nipissing University, Canada.
(2) Ayse Kok, Bogazici University, Istanbul, Turkey.
(3) Anonymous, KTO Karatay University, Turkey.
Complete Peer review History: http://www.sciencedomain.org/review-history/6914

Abstracts

This paper presents dynamic reorganization of peer-to-peer networks to make query routing and content retrieval efficient. The reorganization is conducted which use content similarity information. Unlike other related studies using semantic proximity, the method proposed in this paper relies on folksonomy, which gained wide use in figuring out content similarity in various social networks. The proposed method is designed primarily for flooding-based unstructured P2P networks, however it also can be applied to structured P2P networks such as Tapestry. Simulation-based experiments confirm the effectiveness of the proposed method.

Keywords :

P2P; network reorganization; content similarity; folksonomy.

Full Article - PDF    Page 456-470

DOI : 10.9734/BJMCS/2015/14177

Review History    Comments

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