基于HHO算法的工业无线网状网络节点优化配置与拥塞减少

H. Abdulrab, F. Hussin, A. Awang, I. Ismail, P. Devan, Hussein Shutari
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引用次数: 3

摘要

当谈到提高无线网状网络的性能时,路由器的定位至关重要。为了提供最大的网络可访问性,必须将网状路由器安装在适当的位置。提高网络性能的一种方法是在使用最佳数量的路由器的同时增加覆盖范围。随着时间的推移,科学文献中发展了许多不同的技术,可以优化网络覆盖范围。在这项研究中,一种名为Harris Hawk优化(HHO)的算法被用于优化网状网络中的网状路由器,以优化覆盖范围并减少网络拥塞。HHO识别路由器的最佳位置,以便通过去除重叠的路由器来最小化路由器数量,同时保持最大的覆盖范围,从而获得最佳的网络拓扑。在本研究中,在两种不同的网络拓扑结构中分别部署了60和100个网状路由器。仿真结果与正弦余弦算法(SCA)、灰狼优化(GWO)和粒子群优化(PSO)算法进行了分析比较。在网络覆盖率和减少拥塞方面,仿真结果表明,HHO优于基准算法,覆盖率达到98%,网络规模减少34%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Node Placement and Congestion Reduction in an Industrial Wireless Mesh Network using HHO Algorithm
When it comes to improving the performance of a wireless mesh network, the positioning of routers is critical. In order to provide the greatest network accessibility, it is essential that mesh routers be installed in appropriate locations. One way to improve the network’s performance is to increase the coverage while utilizing an optimum number of routers. The network coverage may be optimised using a number of different techniques that have been developed over time in the scientific literature. An algorithm called Harris Hawk’s Optimization (HHO) is being used in this study to optimally locate mesh routers in a mesh network in order to optimise coverage and reduce network congestion. The HHO identifies the best positions to place the routers in order to have the best possible network topology by removing the overlapping routers to minimize the number of routers while keeping the coverage maximized. In this research, 60, and 100 mesh routers are deployed in two different network topologies. The simulation results are analysed and compared with Sine Cosine Algorithm (SCA), Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithm. With regard to network coverage and congestion reduction, simulation results show that HHO surpasses the benchmark algorithms by having 98% coverage and 34% reduction in the network size.
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