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Heuristic Approach for Optimizing the localization of wireless sensor Networks

机译:优化无线传感器网络定位的启发式方法

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摘要

Wireless Sensor Networks (WSNs) are networks of spatially distributed autonomous nodes used to perform various monitoring tasks. Localization is a challenging issue in WSNs. Many approaches have been proposed to determine the positions of randomly deployed sensor nodes. In this paper, an attempt is made for optimizing the localization of the sensor nodes. A hybrid approach is proposed to improve the efficiency and accuracy and overcome the drawbacks like getting trapped at a local extreme in the optimization process. In the proposed heuristic algorithm the idea of Particle swarm optimization is merged into the chemotaxis of bacterial foraging optimization algorithm to speed up the convergence rate and the elimination probability is selected according to the energy of bacteria to improve the global searching ability. Also the crossover technique of genetic algorithm is introduced in the reproduction stage to improve the evaluation of optimal objective function values.
机译:无线传感器网络(WSN)是空间分布的自治节点的网络,用于执行各种监视任务。在WSN中,本地化是一个具有挑战性的问题。已经提出了许多方法来确定随机部署的传感器节点的位置。在本文中,尝试优化传感器节点的定位。提出了一种混合方法来提高效率和准确性,并克服诸如在优化过程中陷入局部极端的缺点。在提出的启发式算法中,将粒子群算法的思想融入了细菌觅食优化算法的趋化性中,以加快收敛速度​​,并根据细菌的能量选择消除概率,以提高全局搜索能力。在再生阶段还引入了遗传算法的交叉技术,以改善对最佳目标函数值的评估。

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