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

机译:无线传感器网络中复合事件检测的模糊判决方法

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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-dimensionalτ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensionalτ-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(WSNS)中的基本研究之一。由于考虑反映事件状态的各种属性,综合事件与客观世界更加一致。因此,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,我们提出了一个标准来确定复合事件的区域,并在随机部署下提出基于主导的网络拓扑结构算法。为了使事件定义的检测过程和模糊性在自然界中的局部数据的不可靠性,我们提出了一种基于簇的二维τ-气体算法和模糊判决的复合事件决策机制。在大多数节点的感觉数据是正常的情况下,二维τ-气体算法可以有效地滤波故障节点数据,并减少错误数据对事件确定的影响。基于模糊判决的复合事件判断机制具有基于模糊逻辑的算法的优越性;此外,它不需要庞大的规则基础的支持,并且其计算复杂性很小。与收集算法和CDS算法相比,该算法提高了检测精度并减少了流量。

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