ISSN 1000-1239 CN 11-1777/TP

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传感器网络中多近似连续范围查询的处理技术

何文麟 陈 红   

  1. (中国人民大学信息学院 北京 100872) (数据工程与知识工程教育部重点实验室(中国人民大学) 北京 100872) (hewl@ruc.edu.cn)
  • 出版日期: 2010-05-15

Multi-Query Processing Technology of Approximate Continuous Queries in Wireless Sensor Networks

He Wenlin and Chen Hong   

  1. (Information School, Renmin University of China, Beijing 100872) (Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China), Ministry of Education, Beijing 100872)
  • Online: 2010-05-15

摘要: 无线传感器网络为数据库研究开辟了新的研究领域,高效利用节点的有限能量是当前研究的主要目标.如果发布到网络中多个近似连续范围查询不经优化处理而独立执行,会造成节点为不同查询重复发送相同感知数据,从而降低网络寿命.针对近似连续范围查询研究了多查询优化技术,设计了一种索引多维范围查询的多叉树结构rq-kd-tree,通过获取多查询的公共查询部分(查询相交区域)以及基于查询相似度合并相交区域上的多个查询、重写查询.最后,实验证明了所提的算法可以实现能量有效的多查询处理过程.

关键词: 传感器网络, 近似连续范围查询, 多查询优化, rq-kd-tree, 查询重写

Abstract: Wireless sensor networks opens up a fresh research area of database, where efficient use of sensors' limited energy is the primary goal. In general, queries issued to wireless sensor networks are approximate (precise results are not required due to networks' constraint and saving limited energy on sensors), continuous (used to monitor the trend of physical world) and running in parallel. Most studies focus on one aspect of these three features to achieve energy-efficient process in wireless sensor networks. However, if multiple approximate continuous range queries (ACQ) are injected into the networks and run independently without optimization, they will cause a serious problem—sensors are likely to send reduplicate data for different queries and therefore shorten the networks' lifetime. In this paper, the technology of energy-efficiently processing multiple ACQ is studied, and a data structure called rq-kd-tree to index multi-dimensional range queries is designed, which is used to get the common required data of different queries (query intersecting areas). Based on a concept called query similarity degree, original queries are rewritten and issued to the networks. Finally, detailed experiments on both real data and synthetic data are conducted to prove the proposed methods achieving energy-efficient in processing multiple queries.

Key words: sensor networks, approximate continuous range query, multi-query optimization, rq-kd-tree, query rewriting