Proactive replication and search for rare objects in unstructured peer-to-peer networks

Authors:
Guoqiang Gao;Ruixuan Li;Kunmei Wen;Xiwu Gu;Zhengding Lu
Affiliations:
Intelligent and Distributed Computing Lab, College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, P.R. China;Intelligent and Distributed Computing Lab, College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, P.R. China;Intelligent and Distributed Computing Lab, College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, P.R. China;Intelligent and Distributed Computing Lab, College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, P.R. China;Intelligent and Distributed Computing Lab, College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, P.R. China
Venue:
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Year:
2010

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Proactive replication for rare objects in unstructured peer-to-peer networks

Journal of Network and Computer Applications

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Abstract

The search efficiency problem in unstructured peer-to-peer network has not been adequately addressed so far, especially concerning search for rare objects. In this paper, we propose a proactive replication strategy to improve the search efficiency for rare objects. It uses object probing technique for peers to decide whether to establish replications for their objects or not when they join the network. This strategy can effectively increase the popularity of rare objects so as to enhance the search efficiency. We also present a rare object search algorithm. When a peer forwards a search request, forward probability is calculated according to its neighbors' degree and the number of neighbors' objects. Therefore, the search request is forwarded to the peers more likely containing target objects. Simulations show that the proactive replication strategy greatly improves the search efficiency for rare objects with moderate communication overhead. The rare object search algorithm not only improves search efficiency for rare objects, but also achieves load balance in search.