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 × 32 and 64 × 64 grid area, Linear Ranking is good selection operator and offers the best network connectivity and user coverage.
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References
Akyildiz IF, Wang X, Wang W (2005) Wireless mesh networks: a survey. Comput Netw 47(4):445–487
Denzinger J, Kidney J (2006) Evaluating different genetic operators in the testing for unwanted emergent behavior using evolutionary learning of behavior. In: IEEE/WIC/ACM international conference on intelligent agent technology, pp 23–29
Franklin AA, Murthy CSR (2007) Node placement algorithm for deployment of two-tier wireless mesh networks. In: IEEE GLOBECOM-2007, pp 4823–4827
Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NPCompleteness. WH Freeman, San Francisco
Lim A, Rodrigues B, Wang F, Xua Z (2005) k-Center problems with minimum coverage. Theoretical Comput Sci 332(1–3):1–17
Muthaiah SN, Rosenberg C (2008) Single gateway placement in wireless mesh networks. In: 8th international IEEE symposium on computer networks, pp 4754–4759
Odetayo MO (1997) Empirical study of the interdependencies of genetic algorithm parameters. In: 23rd EUROMICRO Conference, New Frontiers of Information Technology, pp 639–643
Tahera K, Ibrahim R, Lochert P (2007) Adopting dynamic operators in a genetic algorithm. In: 9th annual conference on genetic and evolutionary computation, p 1533
Tang M (2009) Gateways placement in backbone wireless mesh networks. Int J Commun Netw Syst Sci 2(1):45–50
Vanhatupa T, Hännikäinen M, Hämäläinen T (2007) Genetic algorithm to optimize node placement and configuration for wlan planning. In: 4th international symposium on wireless communication systems, pp 612–616
Wang J, Xie B, Cai K, Agrawal DP (2007) Efficient mesh router placement in wireless mesh networks. In: MASS-2007, pp 9–11
Xhafa F, Barolli L, Durresi A (2007) An experimental study on genetic algorithms for resource allocation on grid systems. J Interconnect Netw 8(4):427–443
Xhafa F, Duran B, Abraham A, Dahal K (2008) Tuning struggle strategy in genetic algorithms for scheduling in computational grids. Neural Netw World 18(3):209–225
Xhafa F, Sanchez C, Barolli L (2009) Ad hoc and neighborhood search methods for placement of mesh routers in wireless mesh networks. In: ICDCS workshops of the IEEE 29th international conference on distributed computing systems (ICDCS-09), pp 400–405
Yao X (1993) An empirical study of genetic operators in genetic algorithms. In: 19th EUROMICRO symposium on microprocessing and microprogramming on open system design: hardware, software and applications
Acknowledgments
This work is supported by a Grant-in-Aid for scientific research of Japan Society for the Promotion of Science (JSPS). The authors would like to thank JSPS for the financial support.
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Oda, T., Barolli, A., Xhafa, F. et al. WMN–GA: a simulation system for WMNs and its evaluation considering selection operators. J Ambient Intell Human Comput 4, 323–330 (2013). https://doi.org/10.1007/s12652-011-0099-2
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DOI: https://doi.org/10.1007/s12652-011-0099-2