Skip to main content

A Comparison Study of RIWM with RDVM and CM Router Replacement Methods for WMNs Considering Boulevard Distribution of Mesh Clients

  • Conference paper
  • First Online:
Advances in Internet, Data & Web Technologies (EIDWT 2022)

Abstract

The Wireless Mesh Networks (WMNs) have attracted attention for different applications. They are an important networking infrastructure and they have many advantages such as low cost and high-speed wireless Internet connectivity. However, they have some problems such as router placement, covering of mesh clients and load balancing. To deal with these problems, in our previous work, we implemented a hybrid simulation system based on Particle Swarm Optimization (PSO) and Distributed Genetic Algorithm (DGA) called WMN-PSODGA. Moreover, we added in the fitness function a new parameter for the load balancing of the mesh routers called NCMCpR (Number of Covered Mesh Clients per Router). In this paper, we consider Boulevard distribution of mesh clients and three router replacement methods: Random Inertia Weight Method (RIWM), Rational Decrement of Vmax Method (RDVM) and Constriction Method (CM). We carry out simulations using WMN-PSODGA hybrid simulation system and compare the performance of RIWM with RDVM and CM. The simulation results show that RIWM has better loading balancing than RDVM and CM.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Akyildiz, I.F., Wang, X., Wang, W.: Wireless mesh networks: a survey. Comput. Netw. 47(4), 445–487 (2005)

    Article  Google Scholar 

  2. Barolli, A., Sakamoto, S., Ozera, K., Ikeda, M., Barolli, L., Takizawa, M.: Performance evaluation of WMNs by WMN-PSOSA simulation system considering constriction and linearly decreasing Vmax methods. In: Xhafa, F., Caballé, S., Barolli, L. (eds.) 3PGCIC 2017. LNDECT, vol. 13, pp. 111–121. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-69835-9_10

    Chapter  Google Scholar 

  3. Barolli, A., Sakamoto, S., Barolli, L., Takizawa, M.: Performance analysis of simulation system based on particle swarm optimization and distributed genetic algorithm for WMNs considering different distributions of Mesh clients. In: Barolli, L., Xhafa, F., Javaid, N., Enokido, T. (eds.) IMIS 2018. AISC, vol. 773, pp. 32–45. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-93554-6_3

    Chapter  Google Scholar 

  4. Barolli, A., Sakamoto, S., Ozera, K., Barolli, L., Kulla, E., Takizawa, M.: Design and implementation of a hybrid intelligent system based on particle swarm optimization and distributed genetic algorithm. In: Barolli, L., Xhafa, F., Javaid, N., Spaho, E., Kolici, V. (eds.) EIDWT 2018. LNDECT, vol. 17, pp. 79–93. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75928-9_7

    Chapter  Google Scholar 

  5. Clerc, M., Kennedy, J.: The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6(1), 58–73 (2002)

    Article  Google Scholar 

  6. Franklin, A.A., Murthy, C.S.R.: Node placement algorithm for deployment of two-tier wireless Mesh networks. In: Proceedings of Global Telecommunications Conference, pp. 4823–4827 (2007)

    Google Scholar 

  7. Girgis, M.R., Mahmoud, T.M., Abdullatif, B.A., Rabie, A.M.: Solving the wireless Mesh network design problem using genetic algorithm and simulated annealing optimization methods. Int. J. Comput. Appl. 96(11), 1–10 (2014)

    Google Scholar 

  8. Goto, K., Sasaki, Y., Hara, T., Nishio, S.: Data gathering using mobile agents for reducing traffic in dense mobile wireless sensor networks. Mob. Inf. Syst. 9(4), 295–314 (2013)

    Google Scholar 

  9. Inaba, T., Elmazi, D., Sakamoto, S., Oda, T., Ikeda, M., Barolli, L.: A secure-aware call admission control scheme for wireless cellular networks using fuzzy logic and its performance evaluation. J. Mobile Multimed. 11(3&4), 213–222 (2015)

    Google Scholar 

  10. Inaba, T., Obukata, R., Sakamoto, S., Oda, T., Ikeda, M., Barolli, L.: Performance evaluation of a QoS-aware fuzzy-based CAC for LAN access. Int. J. Space-Based Situated Comput. 6(4), 228–238 (2016)

    Article  Google Scholar 

  11. Inaba, T., Sakamoto, S., Oda, T., Ikeda, M., Barolli, L.: A testbed for admission control in WLAN: a fuzzy approach and its performance evaluation. In: BWCCA 2016. LNDECT, vol. 2, pp. 559–571. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-49106-6_55

    Chapter  Google Scholar 

  12. Lim, A., Rodrigues, B., Wang, F., Xu, Z.: k-center problems with minimum coverage. Theoret. Comput. Sci. 332(1–3), 1–17 (2005)

    Article  MathSciNet  Google Scholar 

  13. Maolin, T., et al.: Gateways placement in backbone wireless Mesh networks. Int. J. Commun. Netw. Syst. Sci. 2(1), 44–50 (2009)

    Google Scholar 

  14. Matsuo, K., Sakamoto, S., Oda, T., Barolli, A., Ikeda, M., Barolli, L.: Performance analysis of WMNs by WMN-GA simulation system for two WMN architectures and different TCP congestion-avoidance algorithms and client distributions. Int. J. Commun. Netw. Distrib. Syst. 20(3), 335–351 (2018)

    Google Scholar 

  15. Muthaiah, S.N., Rosenberg, C.P.: Single gateway placement in wireless Mesh networks. In: Proceedings of 8th International IEEE Symposium on Computer Networks, pp. 4754–4759 (2008)

    Google Scholar 

  16. Naka, S., Genji, T., Yura, T., Fukuyama, Y.: A hybrid particle swarm optimization for distribution state estimation. IEEE Trans. Power Syst. 18(1), 60–68 (2003)

    Article  Google Scholar 

  17. Poli, R., Kennedy, J., Blackwell, T.: Particle swarm optimization. Swarm Intell. 1(1), 33–57 (2007). https://doi.org/10.1007/s11721-007-0002-0

    Article  Google Scholar 

  18. Sakamoto, S., Kulla, E., Oda, T., Ikeda, M., Barolli, L., Xhafa, F.: A comparison study of simulated annealing and genetic algorithm for node placement problem in wireless Mesh networks. J. Mobile Multimed. 9(1–2), 101–110 (2013)

    Google Scholar 

  19. Sakamoto, S., Kulla, E., Oda, T., Ikeda, M., Barolli, L., Xhafa, F.: A comparison study of hill climbing, simulated annealing and genetic algorithm for node placement problem in WMNs. J. High Speed Netw. 20(1), 55–66 (2014)

    Article  Google Scholar 

  20. Sakamoto, S., Kulla, E., Oda, T., Ikeda, M., Barolli, L., Xhafa, F.: A simulation system for WMN based on SA: performance evaluation for different instances and starting temperature values. Int. J. Space-Based Situated Comput. 4(3–4), 209–216 (2014)

    Article  Google Scholar 

  21. Sakamoto, S., Kulla, E., Oda, T., Ikeda, M., Barolli, L., Xhafa, F.: Performance evaluation considering iterations per phase and SA temperature in WMN-SA system. Mob. Inf. Syst. 10(3), 321–330 (2014)

    Google Scholar 

  22. Sakamoto, S., Lala, A., Oda, T., Kolici, V., Barolli, L., Xhafa, F.: Application of WMN-SA simulation system for node placement in wireless mesh networks: a case study for a realistic scenario. Int. J. Mobile Comput. Multimed. Commun. (IJMCMC) 6(2), 13–21 (2014)

    Article  Google Scholar 

  23. Sakamoto, S., Oda, T., Ikeda, M., Barolli, L., Xhafa, F.: An integrated simulation system considering WMN-PSO simulation system and network simulator 3. In: BWCCA 2016. LNDECT, vol. 2, pp. 187–198. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-49106-6_17

    Chapter  Google Scholar 

  24. Sakamoto, S., Oda, T., Ikeda, M., Barolli, L., Xhafa, F.: Implementation and evaluation of a simulation system based on particle swarm optimisation for node placement problem in wireless Mesh networks. Int. J. Commun. Netw. Distrib. Syst. 17(1), 1–13 (2016)

    Google Scholar 

  25. Sakamoto, S., Oda, T., Ikeda, M., Barolli, L., Xhafa, F.: Implementation of a new replacement method in WMN-PSO simulation system and its performance evaluation. In: The 30th IEEE International Conference on Advanced Information Networking and Applications (AINA-2016), pp. 206–211 (2016)

    Google Scholar 

  26. Sakamoto, S., Obukata, R., Oda, T., Barolli, L., Ikeda, M., Barolli, A.: Performance analysis of two wireless mesh network architectures by WMN-SA and WMN-TS simulation systems. J. High Speed Netw. 23(4), 311–322 (2017)

    Article  Google Scholar 

  27. Sakamoto, S., Ozera, K., Barolli, A., Ikeda, M., Barolli, L., Takizawa, M.: Implementation of an intelligent hybrid simulation systems for WMNs based on particle swarm optimization and simulated annealing: performance evaluation for different replacement methods. Soft. Comput. 23(9), 3029–3035 (2017)

    Article  Google Scholar 

  28. Sakamoto, S., Ozera, K., Barolli, A., Ikeda, M., Barolli, L., Takizawa, M.: Performance evaluation of WMNs by WMN-PSOSA simulation system considering random inertia weight method and linearly decreasing Vmax method. In: Barolli, L., Xhafa, F., Conesa, J. (eds.) BWCCA 2017. LNDECT, vol. 12, pp. 114–124. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-69811-3_10

    Chapter  Google Scholar 

  29. Sakamoto, S., Ozera, K., Ikeda, M., Barolli, L.: Implementation of intelligent hybrid systems for node placement problem in WMNs considering particle swarm optimization, hill climbing and simulated annealing. Mobile Netw. Appl. 23(1), 27–33 (2017). https://doi.org/10.1007/s11036-017-0897-7

    Article  Google Scholar 

  30. Sakamoto, S., Ozera, K., Ikeda, M., Barolli, L.: Performance evaluation of WMNs by WMN-PSOSA simulation system considering constriction and linearly decreasing inertia weight methods. In: Barolli, L., Enokido, T., Takizawa, M. (eds.) NBiS 2017. LNDECT, vol. 7, pp. 3–13. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-65521-5_1

    Chapter  Google Scholar 

  31. Sakamoto, S., Ozera, K., Oda, T., Ikeda, M., Barolli, L.: Performance evaluation of intelligent hybrid systems for node placement in wireless Mesh networks: a comparison study of WMN-PSOHC and WMN-PSOSA. In: Barolli, L., Enokido, T. (eds.) IMIS 2017. AISC, vol. 612, pp. 16–26. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-61542-4_2

    Chapter  Google Scholar 

  32. Sakamoto, S., Ozera, K., Oda, T., Ikeda, M., Barolli, L.: Performance evaluation of WMN-PSOHC and WMN-PSO simulation systems for node placement in wireless mesh networks: a comparison study. In: Barolli, L., Zhang, M., Wang, X.A. (eds.) EIDWT 2017. LNDECT, vol. 6, pp. 64–74. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-59463-7_7

    Chapter  Google Scholar 

  33. Sakamoto, S., Ozera, K., Barolli, A., Barolli, L., Kolici, V., Takizawa, M.: Performance evaluation of WMN-PSOSA considering four different replacement methods. In: Barolli, L., Xhafa, F., Javaid, N., Spaho, E., Kolici, V. (eds.) EIDWT 2018. LNDECT, vol. 17, pp. 51–64. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75928-9_5

    Chapter  Google Scholar 

  34. Schutte, J.F., Groenwold, A.A.: A study of global optimization using particle swarms. J. Global Optim. 31(1), 93–108 (2005)

    Article  MathSciNet  Google Scholar 

  35. Shi, Y.: Particle swarm optimization. IEEE Connect. 2(1), 8–13 (2004)

    Google Scholar 

  36. Shi, Y., Eberhart, R.C.: Parameter selection in particle swarm optimization. In: Evolutionary Programming VII, pp. 591–600 (1998)

    Google Scholar 

  37. Vanhatupa, T., Hannikainen, M., Hamalainen, T.: Genetic algorithm to optimize node placement and configuration for WLAN planning. In: Proceedings of The 4th IEEE International Symposium on Wireless Communication Systems, pp. 612–616 (2007)

    Google Scholar 

  38. Wang, J., Xie, B., Cai, K., Agrawal, D.P.: Efficient mesh router placement in wireless mesh networks. In: Proceedings of IEEE International Conference on Mobile Adhoc and Sensor Systems (MASS-2007), pp. 1–9 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Barolli, A., Ampririt, P., Sakamoto, S., Kulla, E., Barolli, L. (2022). A Comparison Study of RIWM with RDVM and CM Router Replacement Methods for WMNs Considering Boulevard Distribution of Mesh Clients. In: Barolli, L., Kulla, E., Ikeda, M. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 118. Springer, Cham. https://doi.org/10.1007/978-3-030-95903-6_24

Download citation

Publish with us

Policies and ethics