A simulated annealing algorithm for router nodes placement problem in Wireless Mesh Networks

Abstract

Mesh router nodes placement is a central problem in Wireless Mesh Networks (WMNs). An efficient placement of mesh router nodes is indispensable for achieving network performance in terms of both network connectivity and user coverage. Unfortunately the problem is computationally hard to solve to optimality even for small deployment areas and a small number of mesh router nodes. As WMNs are becoming an important networking infrastructure for providing cost-efficient broadband wireless connectivity, researchers are paying attention to the resolution of the mesh router placement problem through heuristic approaches in order to achieve near optimal, yet high quality solutions in reasonable time. In this work we propose and evaluate a Simulated Annealing (SA) approach to placement of mesh router nodes in WMNs. The optimization model uses two maximization objectives, namely, the size of the giant component in the network and user coverage. Both objectives are important to deployment of WMNs; the former is crucial to

Dynamic router node placement in wireless mesh networks: A PSO approach with constriction coefficient and its convergence analysis

“…Our fitness function in Equation (6) applies the second setting. Note that the previous work [29] for the static network scenario of the WMN-dynRNP problem applies the first setting.…”

“…Similar to [29], we consider the following three cases: . Each mesh router is associated with a circular radio coverage range with radius ∼ U (7,14).…”

“…Note that the deployment area is a grid in [29], meaning that each coordinate is an integer, while the coordinates in our setting are floating-point numbers, which allow for more general applications. For each case, we generate 10 instances, in which the mesh clients are distributed in the deployment area according to a uniform distribution.…”

“…The problem of router node placement (RNP) in WMNs has been studied, e.g., see [4,29,30]. Such a combinatorial optimization problem considers a WMN composed of mesh clients and mesh routers in which mesh routers serve as the access point towards mesh clients and connect to other mesh routers through point-to-point wireless links.…”

“…In our formulation, network connectivity is measured by the size of the greatest component of the topology underlying the WMNs, while client coverage is the number of clients within the radio coverage of mesh routers, which can represent an index of the QoS for the WMNs. Note that most of the previous works focused on solving the static network scenario of our concerned problems by using metaheuristics, e.g., simulated annealing [29] and genetic algorithm [4,30].…”