无线传感器网络中基于时空相关性的数据融合算法
首发时间:2015-12-31
摘要:无线传感器网络(Wireless Sensor Network, WSN)是一种全新的信息获取与处理技术,但是它受到传感器节点硬件的限制,能量问题成为其发展的最大阻碍。利用数据融合技术,根据某种规则,对其感测到的网络数据进行分析与处理,从而达到延长网络生命周期的目的。针对节点密集部署的无线传感器网络,本文提出了基于空间相关性与周期时间特性的数据融合算法。该算法将网络分簇与数据趋势预测相结合,能够有效减少节点能耗、降低数据冗余、延长网络寿命,并通过仿真对比实验进行了验证。
关键词: 无线传感器网络 空间相关性 周期时间相关性 数据融合算法
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Data Aggregation Algorithm Based On Spatio-temporal Correlation In Wireless Sensor Networks
Abstract:Wireless Sensor Network(WSN)is a newly information acquiring and processing technology, it is limited by the sensor's hardware and the energy problem becomes the biggest obstacle of WSN's development. According to certain rules, data aggregation technology can effectively overcome the energy constraint in wireless sensor networks to extend WSN lifetime. In the WSN with sensor nodes deployed densely, the paper presents a data aggregation algorithm based on spatial data correlation and period-temporal correlation. The algorithm combined clustering with data predicting. The simulation results prove that the algorithm can save nodes' energy, reduce data redundancy and extend the network lifetime.
Keywords: Wireless sensor networks spatial correlation period-temporal correlation data aggregation algorithm
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