Skip to Main Content
Efficient and effective full-text retrieval in unstructured peer-to-peer networks remains a challenge in the research community. First, it is difficult, if not impossible, for unstructured P2P search protocols to effectively locate items with guaranteed recall rate. Second, existing schemes to improve search successful rate often rely on replicating a large number of item replicas across the wide area network, incurring a large amount of communication and storage cost. In this paper we propose BloomCast, an efficient and effective full-text retrieval scheme, in unstructured P2P networks. BloomCast is effective because it guarantees perfect recall rate with high probability. It is efficient because the overall communication cost of full-text search is reduced below a formal bound. Furthermore, by casting Bloom Filters instead of the raw documents across the network, BloomCast significantly reduces the communication cost and storage cost for replication. We demonstrate the power of BloomCast design through both mathematical proof and comprehensive simulations. Results show that BloomCast outperforms existing schemes in terms of both recall rate and communication cost.