Optimization of wireless mesh networks planning

Abstract

The main challenge in Wireless Mesh Networks (WMNs) is the deployment issue that has a significant impact on the performance of such networks (coverage, connectivity, load balancing, and throughput), cost, and the capacity to satisfy the Quality of service requirements. In the context of mesh routers placement, the performance of the network is influenced by the number and locations of mesh router, the transmission range of each mesh router, the number of covered clients per mesh router, the size of the deployment area, and the number and weights of mesh clients. The mesh routers placement problem is an NPhard optimization problem, successfully solved using meta-heuristic optimization approaches with reasonable time execution. In this work, we propose three approaches for solving the mesh routers placement problem. The first approach is an improved version of Moth Flame Optimization (MFO), called ECLO-MFO, based on the integration of three strategies including: the Lévy Flight Distribution (LFD) strategy, chaotic map, and the Opposition Based-Learning (OBL) technique to enhance the optimization performance of MFO. The second approach is a hybrid approach, called ASO-SA, based on the combination of global search capability of an Adaptive Snake Optimizer (ASO) with the local search capability of Simulated Annealing (SA). ASO is based on the integration of the Generalized OBL (GOBL) mechanism into the exploration phase of SO. Finally a Binary Whale Optimization Algorithm (BWOA) is suggested to solve the topology planning problem in WMNs. Eight transfer functions divided into two families such as S-shaped and V-shaped are introduced and analyzed to obtain a binary version of WOA