An Optimal Routing Protocol Using a Multiverse Optimizer Algorithm for Wireless Mesh Network

P. Supraja, Anastasia Salameh, R. VaradarajuH., M. Anand, Unggul Priyadi
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引用次数: 2

Abstract

Wireless networks, particularly Wireless Mesh Networks (WMNs), are undergoing a significant change as a result of wireless technology advancements and the Internet's rapid expansion. Mesh routers, which have limited mobility and serve as the foundation of WMN, are made up of mesh clients and form the core of WMNs. Mesh clients can with mesh routers to create a client mesh network. Mesh clients can be either stationary or mobile. To properly utilise the network resources of WMNs, a topology must be designed that provides the best client coverage and network connectivity. Finding the ideal answer to the WMN mesh router placement dilemma will resolve this issue MRP-WMN. Since the MRP-WMN is known to be NP-hard, approximation methods are frequently used to solve it. This is another reason we are carrying out this task. Using the Multi-Verse Optimizer algorithm, we provide a quick technique for resolving the MRP-WMN (MVO). It is also proposed to create a new objective function for the MRP-WMN that accounts for the connected client ratio and connected router ratio, two crucial performance indicators. The connected client ratio rises by an average of 16.1%, 12.5%, and 6.9% according to experiment data, when the MVO method is employed to solve the MRP-WMN problem, the path loss falls by 1.3, 0.9, and 0.6 dB when compared to the Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), correspondingly.
基于多元宇宙优化算法的无线网状网络最优路由协议
随着无线技术的进步和互联网的迅速发展,无线网络,特别是无线网状网络(WMNs)正在发生着重大的变化。Mesh路由器由Mesh客户端组成,是WMN的核心,具有有限的移动性,是WMN的基础。网状客户端可以与网状路由器一起创建一个客户端网状网络。网格客户端可以是固定的也可以是移动的。为了合理利用wmn的网络资源,必须设计一种能够提供最佳客户端覆盖和网络连通性的拓扑结构。为WMN mesh路由器的布局问题找到理想的解决方案将有助于解决MRP-WMN问题。由于已知MRP-WMN是np困难的,因此经常使用近似方法来求解它。这是我们执行这项任务的另一个原因。利用多宇宙优化算法,我们提供了一种快速求解MRP-WMN (MVO)的技术。本文还提出了为MRP-WMN创建一个新的目标函数,该函数考虑了连接的客户端比率和连接的路由器比率这两个关键的性能指标。实验数据显示,采用MVO方法解决MRP-WMN问题时,路径损耗比粒子群优化(PSO)和鲸鱼优化算法(WOA)分别降低了1.3、0.9和0.6 dB,连接客户端比率平均提高了16.1%、12.5%和6.9%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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