Tuning Operators of Genetic Algorithms for Mesh Routers Placement Problem in Wireless Mesh Networks

Abstract

Wireless Mesh Networks (WMNs) have become an important networking infrastructure for providing cost-efficient broadband wireless connectivity. WMNs are showing their applicability in deployment of medical, transport and surveillance applications in urban areas, metropolitan, neighbouring communities and municipal area networks. At the heart of WMNs are the issues of achieving network connectivity and stability as well as QoS in terms of user coverage. These issues are very closely related to the family of node placement problems in WMNs, such as mesh router nodes placement. As these problems are known to be computationally hard to solve, Genetic Algorithms (GAs) have been recently investigated as effective resolution methods. However, GAs require the user to provide values for a number of parameters and a set of genetic operators to achieve the best GA performance for the problem. The task of tuning parameters and operators is complex and, unfortunately, in most cases a specific GA configuration is needed for the problem under study to achieve high quality solutions. In this work we present the results of an experimental study for tuning the parameters and genetic operators of GA for mesh router nodes placement problem. The results of the study suggested a useful combination of parameter values and genetic operators for the problem, which could well serve as a reference for the family of node placement problems in WMNs solved through evolutionary algorithms.