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Hybrid sensor deployment for surveillance and target detection in wireless sensor networks

机译:混合传感器部署,用于无线传感器网络中的监视和目标检测

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Random sensor deployments following Poisson or Gaussian distribution are the most widely adopted deployment strategies for hostile and unpredictable application scenarios such as environment surveillance and malicious mobile target detection. In the literature, researchers assume either Poisson distributed or Gaussian distributed sensors in modeling wireless sensor networks for performance evaluation. This paper instead examines the performance of a wireless sensor network that employs a hybrid random sensor deployment where a set of the sensors are deployed following Poisson distribution and others follow Gaussian distribution around hot spot(s), which are more important than elsewhere and require higher surveillance and target detection capability. The performance of the hybrid wireless sensor network is evaluated in terms of surveillance and target detection probability theoretically and by simulations. The simulation outcomes match with the theoretical results.
机译:遵循泊松或高斯分布的随机传感器部署是针对敌对和不可预测的应用场景(例如环境监视和恶意移动目标检测)的最广泛采用的部署策略。在文献中,研究人员在对无线传感器网络进行建模以进行性能评估时,假设采用泊松分布传感器或高斯分布传感器。相反,本文研究了采用混合随机传感器部署的无线传感器网络的性能,其中,一组传感器按照泊松分布进行部署,而其他传感器遵循热点周围的高斯分布,这比其他地方更重要,并且要求更高监视和目标检测能力。从理论上通过仿真,通过监视和目标检测概率评估混合无线传感器网络的性能。仿真结果与理论结果相符。

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