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BloomCast: Efficient and Effective Full-Text Retrieval in Unstructured P2P Networks
February 2012 (vol. 23 no. 2)
pp. 232-241
Hanhua Chen, Huazhong University of Science and Technology, Wuhan
Hai Jin, Huazhong University of Science and Technology, Wuhan
Xucheng Luo, University of Electronic Science and Technology of China, Chengdu
Yunhao Liu, Tsinghua University, Beijing and Hong Kong University of Science and Technology, Hong Kong
Tao Gu, University of Southern Denmark, Odense M
Kaiji Chen, University of Southern Denmark, Odense M
Lionel M. Ni, Hong Kong University of Science and Technology, Hong Kong and Shanghai Jiao Tong University, Shanghai
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 systems to effectively locate items with guaranteed recall. Second, existing schemes to improve search success rate often rely on replicating a large number of item replicas across the wide area network, incurring a large amount of communication and storage costs. In this paper, we propose BloomCast, an efficient and effective full-text retrieval scheme, in unstructured P2P networks. By leveraging a hybrid P2P protocol, BloomCast replicates the items uniformly at random across the P2P networks, achieving a guaranteed recall at a communication cost of O(\sqrt{N}), where N is the size of the network. Furthermore, by casting Bloom Filters instead of the raw documents across the network, BloomCast significantly reduces the communication and storage costs for replication. We demonstrate the power of BloomCast design through both mathematical proof and comprehensive simulations based on the query logs from a major commercial search engine and NIST TREC WT10G data collection. Results show that BloomCast achieves an average query recall of 91 percent, which outperforms the existing WP algorithm by 18 percent, while BloomCast greatly reduces the search latency for query processing by 57 percent.

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Index Terms:
Peer-to-peer systems, Bloom Filter, replication.
Hanhua Chen, Hai Jin, Xucheng Luo, Yunhao Liu, Tao Gu, Kaiji Chen, Lionel M. Ni, "BloomCast: Efficient and Effective Full-Text Retrieval in Unstructured P2P Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 2, pp. 232-241, Feb. 2012, doi:10.1109/TPDS.2011.168
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