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Probabilistic dynamic distribution of wireless sensor networks with improved distribution method based on electromagnetism-like algorithm

机译:基于类电磁算法的改进分布方法的无线传感器网络概率动态分布

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Performance of the Wireless Sensor Networks (WSNs) depends significantly on coverage area which is determined via the effective dynamic distribution of sensors. Making mobile sensors' dynamic distributions, which determines their positions within the network effectively, improves performances of WSNs by enabling sensors to form the coverage area more efficiently. In this paper, we initially propose the electromagnetism-like (EM) algorithm as the sensor distribution strategy to increase the coverage area of network after random distribution of sensors. Forming more effective coverage area by using mobile and stationary sensors and probabilistic detection model has been aimed by developing the Optimal Sensor Detection Algorithm that is based on the proposed EM algorithm (OSDA-EM). For this purpose, it has been thought that we would attain to more realistic results, with probabilistic detection model by forming the coverage area more effectively. Additionally, performance of the developed OSDA-EM algorithm has been compared with the Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms which was previously used in the dynamic distribution of WSNs. Simulation results have shown that the developed OSDA-EM can be preferred in dynamic distribution of WSNs that performed with probabilistic detection model. (C) 2015 Elsevier Ltd. All rights reserved.
机译:无线传感器网络(WSN)的性能在很大程度上取决于覆盖范围,覆盖范围是通过传感器的有效动态分布来确定的。通过使传感器能够更有效地形成覆盖区域,使移动传感器的动态分布可以有效地确定其在网络中的位置,从而提高WSN的性能。在本文中,我们最初提出了一种类似于电磁(EM)的算法作为传感器分配策略,以在随机分配传感器之后增加网络的覆盖范围。通过开发基于提议的EM算法(OSDA-EM)的最优传感器检测算法,旨在通过使用移动和固定传感器以及概率检测模型来形成更有效的覆盖区域。为此,我们认为通过概率检测模型可以更有效地形成覆盖区域,从而获得更现实的结果。此外,已将开发的OSDA-EM算法的性能与以前用于WSN动态分配的粒子群优化(PSO)和人工蜂群(ABC)算法进行了比较。仿真结果表明,开发的OSDA-EM在以概率检测模型执行的WSN的动态分布中可能是首选。 (C)2015 Elsevier Ltd.保留所有权利。

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