A GA-based System for WMN and its Performance Evaluation for Different Scenarios

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, neighboring communities and municipal area networks. In this paper, we deal with connectivity and coverage problem of WMN. Because these problems are known to be NP-Hard, we propose and implement a system based on Genetic Algorithms (GAs). We evaluate the performance of the proposed system by different scenarios using different metrics such as client distribution, crossover rate, mutation rate, coverage area and giant component. The simulation results show that for 32 x 32 and 64 x 64 grid area, Linear Ranking is good selection operator and offers the best network connectivity and user coverage.