A Node Deployment Optimization Method of Wireless Sensor Network Based on Firefly Algorithm

Wei Liu, Pan Li, Z. Ye, Shuai Yang
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引用次数: 3

Abstract

for making the deployment distribution of wireless sensor network nodes more uniform and improve coverage, this paper proposes a node deployment optimization method based on the firefly algorithm. Firstly, a mathematical model is established to randomly deploy wireless sensor network nodes in the target area, and then the node deployment optimization problem is interpreted as a mathematical issue of searching extreme value; Finally, firefly algorithm is used for optimizing the location of wireless sensor network nodes stochastically deployed in the specified place to obtain this maximum coverage and complete the deployment. Experimental simulation results show that compared with genetic algorithm and particle swarm optimization algorithm, firefly algorithm can better avoid sinking into local optimum and avoid premature convergence. Compared with other two algorithm, the firefly algorithm has a faster search speed, better performance, and better stability.
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基于Firefly算法的无线传感器网络节点部署优化方法
为了使无线传感器网络节点的部署分布更加均匀,提高网络的覆盖率,本文提出了一种基于萤火虫算法的节点部署优化方法。首先建立了在目标区域随机部署无线传感器网络节点的数学模型,然后将节点部署优化问题解释为搜索极值的数学问题;最后,利用萤火虫算法对随机部署在指定地点的无线传感器网络节点进行位置优化,以获得该最大覆盖范围,完成部署。实验仿真结果表明,与遗传算法和粒子群优化算法相比,萤火虫算法能更好地避免陷入局部最优,避免过早收敛。与其他两种算法相比,萤火虫算法具有更快的搜索速度、更好的性能和更好的稳定性。
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