Multi-attribute range queries on top of P2P networks have attracted much attention. Such research has direct application in grid resource monitoring and discovery. In existing research, the overheads (number of hops and number of messages required) of query algorithms depend on both the size of range to be queried and the number of peers, and a high update cost is incurred when resource information changes. We propose a Peer Clustering-based Cache Sharing scheme, in the context of grid computing environments. Peers issuing similar queries are dynamically clustered together, and cached query results are shared among peers. Simulation results show that our scheme improves both query efficiency and update cost. The average number of routing hops and number of messages needed converge to slightly larger than 1, independent of the number of attributes, the size of the range, and the total number of peers. The number of messages needed for attribute update is reduced. The maintenance cost is low.
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