首页> 外文会议>Mobile Data Management: Systems, Services and Middleware, 2009. MDM '09 >Operator Placement for Snapshot Multi-predicate Queries in Wireless Sensor Networks
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Operator Placement for Snapshot Multi-predicate Queries in Wireless Sensor Networks

机译:无线传感器网络中快照多谓词查询的操作员位置

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This work aims at minimize the cost of answering snapshot multi-predicate queries in high-communication-cost networks. High-communication-cost (HCC) networks is a family of networks where communicating data is very demanding in resources, for example in wireless sensor networks transmitting data drains the battery life of sensors involved. The important class of multi-predicate queries in horizontally or vertically distributed databases is addressed. We show that minimizing the communication cost for multi-predicate queries is NP-hard and we propose a dynamic programming algorithm to compute the optimal solution for small problem instances. We also propose a low complexity, approximate, heuristic algorithm for solving larger problem instances efficiently and running it on nodes with low computational power (e.g. sensors). Finally, we present a variant of the Fermat point problem where distances between points are minimal paths in a weighted graph, and propose a solution. An extensive experimental evaluation compares the proposed algorithms to the best known technique used to evaluate queries in wireless sensor networks and shows improvement of 10% up to 95%. The low complexity heuristic algorithm is also shown to be scalable and robust to different query characteristics and network size.
机译:这项工作旨在最大程度地降低在通信成本高的网络中回答快照多谓词查询的成本。高通信成本(HCC)网络是一类网络,其中在资源中对数据的通信要求很高,例如,在无线传感器网络中,传输数据消耗了所涉及传感器的电池寿命。解决了水平或垂直分布的数据库中重要的一类多谓词查询。我们证明了最小化多谓词查询的通信成本是NP-hard的,并且我们提出了一种动态规划算法来为小问题实例计算最优解。我们还提出了一种低复杂度,近似启发式算法,可有效解决较大的问题实例并在计算能力较低的节点(例如传感器)上运行它。最后,我们提出了Fermat点问题的一种变体,其中点之间的距离是加权图中的最小路径,并提出了解决方案。广泛的实验评估将提出的算法与用于评估无线传感器网络中查询的最著名技术进行了比较,并显示出10%到95%的改进。低复杂度启发式算法还显示出可扩展性和鲁棒性,以适应不同的查询特征和网络规模。

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