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Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

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分类：TP393.09[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
作者机构：[1]College of Informnation Science and Engineering, Northeastern University, Shenyang 110004, China, [2]Department of Computer Science, The Hong Kong University of Science and Technology, Hong Kong S.A.R., China, [3]Department of Computer Science, University of Vermnont, Vermont, U.S.A., [4]Department of Computer Science, The University of New South Wales, Australia
相关基金：Supported by the Program for New Century Excellent Talents in Universities （Grant No. NCET-06-0290）, the National Natural Science Foundation of China （Grant Nos. 60503036, and 60773221）, the National High-Tech Development 863 Program of China （Grant No. 2006AA09Z139）, and the Fok Ying Tong Education Foundation Award （Grant No. 104027）.
相关项目：以数据为中心的无线传感器网络查询处理与查询优化技术研究

关键词：计算机网络, 无组织P2P系统, 应答询问, k-NN询问, unstructured P2P, k-NN queries, answering queries, constraints

中文摘要：

我们认为高效地计算的问题散布了地理 k-NN 询问在一未组织对等(P2P ) 系统，各个在凝视被一个单个组织管理并且能仅仅与它的逻辑附近的同伴交流。如此的询问基于本地过滤器比存在散布 k-NN 询问查询统计，并且要求尽可能少的通讯花费了，它使它更困难。特别，我们希望通讯花费了到还原剂候选人同伴并且降级。在这篇论文，我们建议一种有效修剪技术最小化要处理回答 k-NN 询问的候选人同伴的数字。当更新同伴时，我们的途径对连续 k-NN 询问，动态地离开或加入，并且更新在一个同伴的数据同伴特别合适，包括改变同伴的范围。另外，模拟结果证明建议途径超过质问接近的基于的存在最小的跳矩形(MBR ) ，特别为连续询问。这篇文章(doi:10.1007/s11390-008-9151-x ) 的联机版本包含增补材料，它对授权用户可得到。

英文摘要：

We consider the problem of efficiently computing distributed geographical k-NN queries in an unstructured peer-to-peer （P2P） system, in which each peer is managed by an individual organization and can only communicate with its logical neighboring peers. Such queries are based on local filter query statistics, and require as less communication cost as possible which makes it more difficult than the existing distributed k-NN queries. Especially, we hope to reduce candidate peers and degrade communication cost. In this paper, we propose an efficient pruning technique to minimize the number of candidate peers to be processed to answer the k-NN queries. Our approach is especially suitable for continuous k-NN queries when updating peers, including changing ranges of peers, dynamically leaving or joining peers, and updating data in a peer. In addition, simulation results show that the proposed approach outperforms the existing Minimum Bounding Rectangle （MBR）-based query approaches, especially for continuous queries.

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