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机构地区:[1]江苏大学计算机科学与通信工程学院,江苏镇江212013
出 处:《上海交通大学学报》2014年第10期1457-1460,1467,共5页Journal of Shanghai Jiaotong University
基 金:国家科技型中小企业技术创新基金(13C26213201857);江苏省科技型企业技术创新基金(BC2012210)
摘 要:提出了一种基于节点剪枝的Top-k査询算法.定义集合支配区域与剪枝规则,根据用户查询位置的变动,按照给定的剪切规则,对传感器网络节点进行剪枝处理,将符合规则的节点预先筛除,运用统计学抽样理论,设计了空间关键字近似Top-k查询算法.在2个真实数据集上进行验证.实验结果表明,该算法能够满足传感器网络环境中用户的需求,并且相比于边界距离增量算法(IBD)与基于改进的MW-Voronoi区域的空间关键字查询算法(MSK-uvr),其网络通信开销较低.In this paper, a Top-k query algorithm based on node pruning rules was proposed. The concept of a set dominate region and pruning rules were defineded. As the position of users change in the dynamic set dominate region, the nodes of wireless sensor networks were pruned which conformed to pruning rules. The statistical sampling theory was used to design an approximate Top k query algorithm based on spatial keyword. Experiments on two real datasets were made to validate the effect of the algorithm. The results show that the algorithm meets the needs of users in sensor network environment and it has an advantage of low energy consumption compared to the incremental border distance (IBD) algorithm and query algorithm of spatial keyword based upgraded MW-Voronoi region (MSK-uvr).
关 键 词:空间关键字查询 TOP-K 传感器网络 支配区域
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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