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A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

机译:无线传感器网络中基于模糊决策的复合事件检测方法

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摘要

The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic.
机译:事件检测是无线传感器网络(WSN)的基础研究之一。由于考虑到反映事件状态的各种属性,因此复合事件与客观世界更加一致。因此,对复合事件的研究变得更加现实。在本文中,我们分析了复合事件的特征;然后提出了确定复合事件区域的准则,并提出了在随机部署下基于支配集的网络拓扑构建算法。针对部分数据在检测过程中的不可靠性和事件定义的模糊性,提出了一种基于聚类的二维τ-GAS算法和基于模糊决策的复合事件决策机制。在大多数节点的传感数据正常的情况下,二维τ-GAS算法可以有效地过滤故障节点数据,减少错误数据对事件确定的影响。基于模糊决策的复合事件判断机制具有基于模糊逻辑的算法的优越性。而且,它不需要庞大的规则库的支持,并且其计算复杂度很小。与CollECT算法和CDS算法相比,该算法提高了检测精度,减少了流量。

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