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A genetic algorithm-based system for wireless mesh networks: analysis of system data considering different routing protocols and architectures

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Abstract

Wireless mesh networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In our previous work, we evaluated WMN-GA system which is based on genetic algorithms (GAs) to find an optimal location assignment for mesh routers. In this paper, we evaluate the performance of four different distributions of mesh clients for two WMN architectures considering throughput, delay and energy metrics. For simulations, we used ns-3, optimized link state routing (OLSR) and hybrid wireless mesh protocols (HWMP). We compare the performance for Normal, Uniform, Exponential and Weibull distributions of mesh clients by sending multiple constant bit rate flows in the network. The simulation results show that for HWM protocol the throughput of Uniform distribution is higher than other distributions. However, for OLSR protocol, the throughput of Exponential distribution is better than other distributions. For both protocols, the delay and remaining energy are better for Weibull distribution.

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References

  • Barolli L (2007) An intelligent call admission control system for wireless cellular networks based on fuzzy logic. J Mob Multimed 3(4):331–346

    Google Scholar 

  • Clausen T, Jacquet P (2003) Optimized link state routing protocol (olsr). RFC 3626 (Experimental)

  • 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

  • Draves R, Padhye J, Zill B (2004) Comparison of routing metrics for static multi-hop wireless networks. SIGCOMM’ 04:133–144

    Article  Google Scholar 

  • Franklin A, Murthy C (2007) Node placement algorithm for deployment of two-tier wireless mesh networks. IEEE GLOBECOM-2007, pp 4823–4827

  • IEEE 802.11 (2007) Wireless lan medium access control (mac) and physical layer (phy) specifications, IEEE Computer Society Std., [Online]. http://standards.ieee.org/getieee802/download/802.11-2007.pdf

  • Ikeda M, Oda T, Kulla E, Hiyama M, Barolli L, Younas M (2012) Performance evaluation of wmn considering number of connections using ns-3 simulator. In: The third international workshop on methods, analysis and protocols for wireless communication (MAPWC 2012), pp 498–502

  • Kulla E, Oda T, Barolli L (2014) A fuzzy-based method for selection of actor nodes in wireless sensor and actor networks. In: 9th international conference on broadband and wireless computing, communication and applications (BWCCA), pp 1–7

  • Lim A, Rodrigues B, Wang F, Xu Z (2005) k-center problems with minimum coverage. Theor Comput Sci 332:1–17

    Article  MathSciNet  MATH  Google Scholar 

  • Muthaiah SN, Rosenberg CP (2008)Single gateway placement in wireless mesh networks. In: 8th international IEEE symposium on computer networks, pp 4754–4759

  • Nordstrom E (2002) Ape—a large scale ad hoc network testbed for reproducible performance tests. Master thesis, Uppsala University

  • Oda T, Barolli A, Xhafa F, Barolli L, Ikeda M, Takizawa M (2013) WMN-GA: a simulation system for wmns and its evaluation considering selection operators. J Ambient Intell Humaniz Comput JAIHC 4(3):323–330

    Article  Google Scholar 

  • Oda T, Sakamoto S, Barolli A, Ikeda M, Barolli L, Xhafa F (2014) A GA-based simulation system for wmns: performance analysis for different wmn architectures considering tcp. In: 9th international conference on broadband and wireless computing, communication and applications (BWCCA), pp 120–126

  • Odetayo M (1997) Empirical study of the interdependencies of genetic algorithm parameters. In: 23rd EUROMICRO conference, New Frontiers of Information Technology, pp 639–643

  • Palmieri F, Castiglione A (2012) Condensation-based routing in mobile ad-hoc networks. J Mob Inf Syst 8(3):199–211

    Google Scholar 

  • Palmieri F (2013) Scalable service discovery in ubiquitous and pervasive computing architectures: a percolation-driven approach. J Futur Gen Comput Syst 29(3):693–703

    Article  Google Scholar 

  • Perkins C, Belding-Royer E, Das S (2003) Ad hoc on-demand distance vector (aodv) routing. RFC 3561 (Experimental)

  • Tang M (2009) Gateways placement in backbone wireless mesh networks. Int J Commun Netw Syst Sci 2(1):44–50

    Google Scholar 

  • Vanhatupa T, Hannikainen M, Hamalainen 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 D (2007) Efficient mesh router placement in wireless mesh networks. 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

    Article  Google Scholar 

  • Xhafa F, Duran B, Abrahamy A, Daha K (2008) Tuning struggle strategy in genetic algorithms for scheduling in computational grids. Neural Netw World 18(3):209–225

    Google Scholar 

  • Xhafa F, Sanchez C, Barolli L (2009) Locals search algorithms for efficient router nodes placement in wireless mesh networks. In: International conference on network-based information systems (NBiS-2009), pp 572–579

  • Yao X (1993) An empirical study of genetic operators in genetic algorithms. In: EUROMICRO 93 19th EUROMICRO symposium on microprocessing and microprogramming on open system design: hardware, software and applications, pp 707–714

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Acknowledgments

This work is supported by a Grant-in-Aid for Scientific Research from Japanese Society for the Promotion of Science (JSPS). The authors would like to thank JSPS for the financial support.

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Correspondence to Tetsuya Oda.

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Communicated by V. Loia.

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Oda, T., Elmazi, D., Barolli, A. et al. A genetic algorithm-based system for wireless mesh networks: analysis of system data considering different routing protocols and architectures. Soft Comput 20, 2627–2640 (2016). https://doi.org/10.1007/s00500-015-1663-z

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