高效全文检索与保证召回的非结构化p2p

Hanhua Chen, Hai Jin, Xucheng Luo, Yunhao Liu, L. Ni
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引用次数: 3

摘要

在非结构化点对点网络中实现高效的全文检索一直是研究领域面临的挑战。首先,非结构化P2P搜索协议很难(如果不是不可能的话)有效地定位具有保证召回率的项目。其次,现有的提高搜索成功率的方案往往依赖于在广域网中复制大量的条目副本,这会产生大量的通信和存储成本。本文提出了一种在非结构化P2P网络中高效的全文检索方案BloomCast。BloomCast是有效的,因为它保证了高概率的完美召回率。它是高效的,因为全文搜索的总体通信成本降低到一个正式的界限以下。此外,通过在网络上使用Bloom Filters而不是原始文档,BloomCast显著降低了复制的通信成本和存储成本。我们通过数学证明和综合模拟来展示BloomCast设计的强大功能。结果表明,该方法在召回率和通信成本方面都优于现有方案。
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BloomCast: Efficient Full-Text Retrieval over Unstructured P2Ps with Guaranteed Recall
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.
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