A hybrid intelligent system for wireless mesh networks: assessment of implemented system for two instances and three router replacement methods using <i>V</i><SUB align="right">max parameter
Shinji Sakamoto
Abstract
Wireless mesh networks (WMNs) are a good choice for internet of things (IoT) and edge computing due to their good scalability, robustness and maintainability. In this research work, we introduce a hybrid intelligent system that integrates particle swarm optimisation (PSO) and hill climbing (HC) called WMN-PSOHC. We assess the performance of WMN-PSOHC system for three different router replacement methods: the linearly decreasing Vmax method (LDVM), the rational decrement of Vmax method (RDVM), and the fast convergence RDVM (FC-RDVM) considering Vmax parameter. We consider two scenarios for small and middle scale WMNs which we call instances 1 and 2. The simulation results show that compared with LDVM and RDVM, the FC-RDVM performs better for both instances 1 and 2.