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Immigrant imperialist competitive algorithm to solve the multi-constraint node placement problem in target-based wireless sensor networks

机译:移民帝国主义竞争算法,解决基于目标的无线传感器网络中的多约束节点放置问题

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The k-coverage and m-connected sensor placement problem in target-based wireless sensor networks (WSNs) is assessed here, where all target points must be covered by at least k sensor nodes and all senor nodes must be connected to the sink through at least m separate paths. The potential positions for placing sensor nodes are pre-specified. A new method based on the imperialist competitive algorithm (ICA) is proposed to solve this dual featured problem. The possibility of immigration for colonies from weak to stronger empires is added to the standard ICA. Immigration promotes the ability of the Immigrant imperialist competitive algorithm (IICA) in exploration and prevents the early convergence to local minimums. The mathematical formulation is provided for the immigration process. In simulations, the 2D and 3D environments together with grid and random WSNs are of concern. The main issues of concern here consist of the placed sensor node count and the run time. The experimental results indicate that this proposed method applies less sensor nodes than its counterparts and requires less run time. (C) 2020 Elsevier B.V. All rights reserved.
机译:此处评估基于目标的无线传感器网络(WSNS)中的K-Coverage和M连接的传感器放置问题,其中所有目标点必须由至少k传感器节点覆盖,并且所有传感器节点必须通过AT连接到接收器至少M个单独的路径。预先指定放置传感器节点的潜在位置。提出了一种基于帝国主义竞争算法(ICA)的新方法来解决这个双重特色问题。从弱到更强大的帝国的殖民地移民的可能性被添加到标准ICA中。移民局促进移民帝国主义竞争算法(IICA)在勘探中的能力,并阻止早期收敛到局部最低限度。为移民过程提供数学制定。在仿真中,2D和3D环境与网格和随机WSN一起关注。这里关注的主要问题包括放置的传感器节点计数和运行时。实验结果表明,该方法应用于较少的传感器节点,而不是对应物,并且需要较少的运行时间。 (c)2020 Elsevier B.v.保留所有权利。

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