Abstract
Wireless Mesh Networks (WMNs) currently have a lot of attention in wireless research and technology community due to their importance for providing cost-efficient broadband connectivity. Issues for achieving the network connectivity and user coverage are related with the node placement problem. In this work, we consider the router node placement problem in WMNs. We want to find the most optimal distribution of router nodes in order to provide the best network connectivity and provide the best client coverage in a set of uniformly distributed clients. We use our WMN-SA simulation system to calculate the size of Giant Component (GC) and number of covered users with different number of iterations per phase of Simulated Annealing (SA) algorithm calculations. From results, SA is good algorithm for optimizing the size of GC. While in terms of number of covered users, it does not cover all users. The performance of WMN-SA system increases when we use more iterations per phase.
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Notes
- 1.
Initial solution, fitness evaluation and movement types are the same for Hill Climbing and Simulated Annealing
References
Akyildiz F, Wang X, Wang W (2005) Wireless mesh networks: a survey. Comput Netw 47(4):445–487
Nandiraju N, Nandiraju D, Santhanama L, He B, ,Wang J and Agrawal D (2007) Wireless mesh networks: current challenges and future direction of web-in-the-sky. IEEE Wireless Commun,pp 79–89
Chen Ch, Chekuri Ch (2007) Urban wireless mesh network planning: the case of directional antennas. Tech report no. UIUCDCS-R-2007-2874, Department of computer science, University of Illinois at urbana-champaign
Garey MR, Johnson DS (1979) Computers and intractability : a guide to the theory of np-completeness. Freeman, San Francisco
Lim B, Rodrigues F, Wang, Xua Zh (2005) k- center problems with minimum coverage. Theoret Comput Sci 332(1-3):1–17
Amaldi E, Capone A, Cesana M, Filippini I, Malucelli F (2008) Optimization models and methods for planning wireless mesh networks. Comput Netw 52:2159–2171
Wang J, Xie B, Cai K, Agrawal DP (2007) Efficient mesh router placement in wireless mesh networks. In: Proceedings of MASS-2007, Pisa, Italy, pp 9–11
Muthaiah SN,Rosenberg C (2008) Single gateway placement in wireless mesh networks. In: Proceedings of 8th international IEEE symposium on computer networks, Turkey, pp 4754–4759
Zhou P, Manoj BS, Rao RA (2007) Gateway placement algorithm in wireless mesh networks. In: Proceedings of the 3rd annual international wireless internet conference (WICON-2007), pp 1–9
Tang M (2009) Gateways placement in backbone wireless mesh networks. Int J Commun Net Syst Sci 2(1):45–50
Franklin A and Siva Ram Murthy C (2007) Node placement algorithm for deployment of two-tier wireless mesh networks. In: Proceedings of IEEE GLOBECOM-2007, Washington, USA, pp 4823–4827
Vanhatupa T, Hannikainen M and Hamalainen TD (2007) Genetic algorithm to optimize node placement and configuration for WLAN planning. In: Proceedings of 4th international symposium on wireless communication systems, pp 612–616
Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. J Sci 220:671–680
Xhafa F, Sanchez Ch, Barolli L, Miho R (2010) An annealing approach to router nodes placement problem in wireless mesh networks In: Proceedings of CISIS-2010, pp 245–252
Holland J (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor
Xhafa F, Sanchez C, Barolli L, (2010) Genetic algorithms for efficient placement of router nodes in wireless mesh networks.In: Proceedings of AINA 2010, pp 465–472
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Sakamoto, S., Oda, T., Kulla, E., Ikeda, M., Barolli, L., Xhafa, F. (2013). Performance Evaluation of WMNs Using Simulated Annealing Algorithm Considering Different Number Iterations per Phase and Normal Distribution. In: Park, J.J., Barolli, L., Xhafa, F., Jeong, H.Y. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_18
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DOI: https://doi.org/10.1007/978-94-007-6996-0_18
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