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Cluster adaptation method to enhance performance of filtering scheme in sensor networks

机译:增强传感器网络滤波方案性能的集群自适应方法

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Sensor networks are the next generation of technology for use in various applications, including tracking, monitoring and control. However, sensor networks still have some inherent security and hardware problems. The cluster routing scheme has been proposed in attempt to reduce duplication reports. Moreover, statistical en-route filtering (SEF) has been proposed to detect and drop the injected fabricated report found in the sensor network. When SEF method is applied in cluster-based sensor networks, their detection capabilities may be quite poor because the proposed schemes do not consider each possible feature that may be present. To solve this problem, we propose a cluster adaptation method to enhance the performance of SEF. The proposed method uses a fuzzy logic approach to form an efficient cluster for SEF. The sufficient performance of the proposed method is shown by the simulation results.
机译:传感器网络是用于各种应用(包括跟踪,监视和控制)的下一代技术。但是,传感器网络仍然存在一些固有的安全性和硬件问题。已经提出了集群路由方案,以试图减少重复报告。此外,已经提出了统计途中过滤(SEF)来检测并丢弃在传感器网络中发现的注入的伪造报告。当SEF方法应用于基于群集的传感器网络时,它们的检测能力可能会很差,因为建议的方案没有考虑可能存在的每个可能特征。为了解决这个问题,我们提出了一种集群自适应的方法来提高SEF的性能。所提出的方法使用模糊逻辑方法来形成SEF的有效集群。仿真结果表明了该方法的足够性能。

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