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Bio-Inspired WSN Architecture: Event Detection and Localization in a Fault Tolerant WSN

机译:生物启发WSN架构:容错WSN中的事件检测和本地化

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One can think of human body as a sensory network. In particular, skin has several neurons that provide the sense of touch with different sensitivities, and neurons for communicating the sensory signals to the brain. Even though skin might occasionally experience some lacerations, it performs remarkably well (fault tolerant) with the failure of some sensors. One of the challenges in collaborative wireless sensor networks (WSN) is fault tolerant detection and localization of targets. In this paper we present a biologically inspired architecture model for WSN. Diagnosis of sensors in WSN model presented here is derived from the concept of the immune system. We present an architecture for WSN for detection and localization of multiple targets inspired by human nervous system. We show that the advantages of such bio-inspired networks are reduced data for communication, self-diagnosis to detect faulty sensors in real-time and the ability to localize events. We present the results of our algorithms on simulation data.
机译:人们可以将人体视为一个感官网络。特别是,皮肤具有几个神经元,其提供不同的敏感性的触感和神经元,用于将感官信号传送到大脑。即使皮肤可能偶尔会遇到一些撕裂,它也具有显着良好的(容错),具有一些传感器的故障。协作无线传感器网络(WSN)中的挑战之一是目标的容错检测和定位。在本文中,我们为WSN提供了一种生物学启发的架构模型。这里呈现的WSN模型中传感器的诊断来自免疫系统的概念。我们为WSN提供了一种架构,用于检测和定位由人类神经系统启发的多个目标。我们表明,这种生物启发网络的优点是减少通信数据,自我诊断,以实时检测故障传感器以及本地化事件的能力。我们介绍了我们对模拟数据的算法的结果。

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