Peer-to-peer systems have emerged as a popular way to share huge volumes of data. The usability of these systems depends on effective techniques to find and retrieve data; however, current techniques used in existing P2P systems are often very inefficient. In this paper, we present three techniques for efficient search in P2P systems. We present the design of these techniques, and then evaluate them using a combination of analysis and experiments over Gnutella, the largest open P2P system in operation. We show that while our techniques maintain the same quality of results as currently used techniques, they use up to 5 times fewer resources. In addition, we designed our techniques to be simple, so that they can be easily incorporated into existing systems for immediate impact.

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We identify crucial design issues in building a distributed inverted index for a large collection of web pages. We introduce a novel pipelining technique for structuring the core index-building system that substantially reduces the index construction time. We also propose a storage scheme for creating and managing inverted files using an embedded database system. We suggest and compare different strategies for collecting global statistics from distributed inverted indexes. Finally, we present performance results from experiments on a testbed distributed indexing system that we have implemented.

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