Abstract
The maximum distance from the access points to the nearest gateways determines the network time delay, and has an important effect on network performance in wireless mesh networks. Motivated by the gateway deployment problem, this study is focused on optimizing the gateway deployment by minimizing the maximum distance. This is done by first improving upon theorems so that the plane can be divided into several intersecting regions; vertices locate in the same region are equivalent and can connect the same access points; the coordinates of the regions can also be determined. Then, maximum coupling subgraph is used in order to recognize the maximum intersecting regions; meanwhile, the coordinates are calculated by representative points. Lastly, an RPSO algorithm is designed in which representative points are taken as the initial particles to search the optimal gateway deployment. The simulation results demonstrate that the optimal gateway deployment, as determined by the RPSO algorithm process, has a smaller coverage radius, a more stable result and a faster convergence rate as compared to other algorithms.







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Akyildiz IF, Wang XD, Wang WL (2005) Wireless mesh networks: a survey. Comput Netw 47(4):445–487
Ali YMB (2011) An augmented particle swarm model based bi-acceleration factor. Int J Intel Comput Cybern 4(2):187–205
Aoun B, Boutaba R, Iraqi Y, Kenward G (2006) Gateway placement optimization in wireless mesh networks with QoS constraints. IEEE J Sel Areas Commun 24(11):2127–2136
Bejerano Y (2004) Efficient integration of multihop wireless and wired networks with QoS constraints. IEEE/ACM Trans Netw 12(6):1064–1078
Breu H, Kirkpatrick D (1998) Unit disk graph recognition is NP-hard. Comput Geom Theory Appl 9(1/2):3–24
Bruno R, Conti M, Gregori E (2005) Mesh networks: commodity multihop ad hoc networks. IEEE Commun Mag 43(3):123–131
Clerc M, Kennedy J (2003) The particle swarm-explosion, stability, and convergence analysis and parameter selection. Inf Process Lett 85(6):317–325
Durocher S, Jampani KR, Lubiw A et al (2011) Modeling gateway deployment in wireless networks: geometrick-centres of unit disc graphs. Comput Geom 44:286–302
Durocher S, Jampani KR, Lubiw A, et al (2008) Modelling gateway deployment in wireless networks: geometric k-centres of unit disc graphs. In: Proceedings of the fifth international workshop on foundations of mobile computing. ACM, pp 79–86
Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, pp 39–43
He B, Xie B, Agrawal DP (2008) Optimizing deployment of Internet gateway in wireless mesh networks. Comput Commun 31(7):1259–1275
Huang SQ, Wang GC, Zhang Z et al (2013) A method of geometric-center gateway deployment of wireless mesh networks. Chin J Comput 36(7):1475–1484
Huang SQ, Wang GC, Shan ZG et al (2014) Node deployment optimization of wireless network in smart cit. J Comput Dev 51(2):274–289
Kenney J (1999) Small worlds and mega-minds effects of neighborhood topology on particle swarm performance. In: proceedings of IEEE Congress on Evolutionary Computation. Piscataway, NJIEEE Service Center, pp 1931–1938
Megiddo N, Supowit KJ (1984) On the complexity of some common geometric location problems. SIAM J Comput 13(1):182–196
Oda T, Elmazi D, Barolli A, Sakamoto S, Barolli L, Fatos X (2015) A genetic algorithm-based system for wireless mesh networks: analysis of system data considering different routing protocols and architectures. Soft Comput. http://link.springer.com/article/10.1007/s00500-015-1663-z. Accessed 31 Mar 2015
Papadaki K, Friderikos V (2010) Gateway selection and routing in wireless mesh networks. Comput Netw 54(2):319–329
Plesnik J (1980) On the computational complexity of centers locating in a graph. Appl Math 25(6):445–452
Seyedzadegan M, Othman M, Ali BM (2013) Zero-degree algorithm for internet gateway deployment in backbone wireless mesh networks. J Netw Comput Appl 36(6):1705–1723
Shi Y, Eberhart RC (2001) Empirical study of particle swarm optimization. In: Proceedings of IEEE Congress on Evolutionary Computation, pp 94–100
Srivastava JR, Sudarshan TSB (2014) Energy-efficient cache node placement using genetic algorithm in wireless sensor networks. Soft Comput. http://link.springer.com/article/10.1007/s00500-014-1473-8. Accessed 08 Oct 2014
Targon V, Sanso B, Capone A (2010) The joint gateway deployment and spatial reuse problem in wireless. Comput Netw 54(7):231–240
Thai MT, Zhang N, Tiwari R (2007) On approximation algorithms of k-connected m-dominating sets in disk graphs. Theor Comput Sci. 385(1/2/3): 49–59
Wu WL, Du HW, Jia XH (2006) Minimum connected dominating sets and maximal independent sets in unit disk graphs. Theor Comput Sci. 352(1/2/3): 1–7
Zhou Z, Shi Y (2011) Inertia weight adaptation in particle swarm optimization algorithm. Advances in swarm intelligence. Springer, Berlin, pp 71–79
Acknowledgments
This study is supported by National Natural Science Fund of China (Grant No. 61373125), the National High Technology Research and Development Program of China under Grant (No. 2013AA040404), the Fundamental Research Funds for the Central Universities (Nos. 21615439, 21615443), Guangdong Province Natural Science Foundation (No. 2014A030313386), Guangdong Universities Scientific Innovation Project (No. 2013KJCX0018).
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Communicated by V. Loia.
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Li, Y., Huang, S., Fan, R. et al. Research on gateway deployment of WMN based on maximum coupling subgraph and PSO algorithm. Soft Comput 21, 923–933 (2017). https://doi.org/10.1007/s00500-015-1822-2
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DOI: https://doi.org/10.1007/s00500-015-1822-2