A Complex Event Detection Algorithm Based on Correlation Analysis
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摘要: 针对无线传感器网络中传统事件检测算法所存在的网络传输量大和能耗高的问题，提出了一种基于模式匹配与相关性分析的复杂事件检测算法.根据复杂事件的特点，算法将事件检测分为单个节点处的特征检测和多个节点之间相关性分析两部分：在单个节点进行特征提取和模式匹配；多节点间通过对数据进行变换压缩和相关性分析来减少网络传输量从而降低能耗.实验表明，提出的复杂事件检测算法能够有效地减少能量消耗.Abstract: In wireless sensor networks, the traditional event detection algorithm has the problem of high network transmission and energy consumption. In order to solve such problem, this paper presents a new complex event detection algorithm based on pattern matching and correlation analysis. Complex events not only change the data of a single node, but also be the impact of the entire sensor network. So it is often manifested as a particular pattern at the sensor node and the correlation between nodes satisfy some relationship. According to the characteristics of complex event showed, event detection is divided into two parts: the feature detection at single node and the correlation analysis between multiple nodes. Calculation pressure is allocated to each node by the feature extraction and pattern matching. So the algorithm can control the frequency of the calculation of the correlation analysis, and it will extend the network lifetime. In order to reduce the amount of network traffic, the compressed data is used for correlation analysis. The experiments show that the proposed algorithm can effectively reduce energy consumption.
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