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Improved whale optimization algorithm and its application in heterogeneous wireless sensor networks

机译:改进鲸鲸优化算法及其在异构无线传感器网络中的应用

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Aiming at the problems of node redundancy and network cost increase in heterogeneous wireless sensor networks, this article proposes an improved whale optimization algorithm coverage optimization method. First, establish a mathematical model that balances node utilization, coverage, and energy consumption. Second, use the sine–cosine algorithm to improve the whale optimization algorithm and change the convergence factor of the original algorithm. The linear decrease is changed to the nonlinear decrease of the cosine form, which balances the global search and local search capabilities, and adds the inertial weight of the synchronous cosine form to improve the optimization accuracy and speed up the search speed. The improved whale optimization algorithm solves the heterogeneous wireless sensor network coverage optimization model and obtains the optimal coverage scheme. Simulation experiments show that the proposed method can effectively improve the network coverage effect, as well as the utilization rate of nodes, and reduce network cost consumption.
机译:旨在在异构无线传感器网络中节点冗余和网络成本增加的问题,本文提出了一种改进的鲸料优化算法覆盖优化方法。首先,建立一个数学模型,使节点利用率,覆盖率和能量消耗进行平衡。其次,使用正弦余弦算法来提高鲸瓦优化算法,改变原始算法的收敛因素。线性减小改变为余弦形式的非线性减少,这使得全局搜索和本地搜索能力平衡,并增加了同步余弦形式的惯性权重,以提高优化精度并加快搜索速度。改进的鲸井优化算法解决了异构无线传感器网络覆盖优化模型,并获得最佳覆盖方案。仿真实验表明,该方法可以有效地改善网络覆盖效应,以及节点的利用率,降低网络成本消耗。

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