A scalable multi-attribute range query approach on cluster-based hybrid overlays

Authors:
You-Fu Yu;Po-Jung Huang;Quan-Jie Chen;Tian-Liang Huang;Kuan-Chou Lai
Affiliations:
Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.
Venue:
MTPP'10 Proceedings of the Second Russia-Taiwan conference on Methods and tools of parallel programming multicomputers
Year:
2010

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Abstract

Resource discovery in distributed computing systems is a critical issue to find and retrieve distributed resources rapidly. In general, most of previous proposed strategies focus on developing keyword searching approaches with preserving system scalability. In this paper, we propose a cluster-based hybrid overlay, which supports efficient keyword searching with the highly churn rate. The cluster-based hybrid overlay groups the nodes with the same attributes to form unstructured attribute-groups, and then clusters these attribute-groups with similar attributes to form attribute-clusters. Our proposed hybrid overlay could provide efficient multi-attribute and range-query searches with load balancing in large-scale P2P networks. Experimental results show that the proposed overlay performs well.