iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://doi.org/10.1007/978-94-007-6996-0_18
Performance Evaluation of WMNs Using Simulated Annealing Algorithm Considering Different Number Iterations per Phase and Normal Distribution | SpringerLink
Skip to main content

Performance Evaluation of WMNs Using Simulated Annealing Algorithm Considering Different Number Iterations per Phase and Normal Distribution

  • Conference paper
Information Technology Convergence

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 253))

  • 1133 Accesses

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.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover 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

Similar content being viewed by others

Notes

  1. 1.

    Initial solution, fitness evaluation and movement types are the same for Hill Climbing and Simulated Annealing

References

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

    Article  Google Scholar 

  2. 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

    Google Scholar 

  3. 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

    Google Scholar 

  4. Garey MR, Johnson DS (1979) Computers and intractability : a guide to the theory of np-completeness. Freeman, San Francisco

    Google Scholar 

  5. Lim B, Rodrigues F, Wang, Xua Zh (2005) k- center problems with minimum coverage. Theoret Comput Sci 332(1-3):1–17

    Google Scholar 

  6. 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

    Article  Google Scholar 

  7. 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

    Google Scholar 

  8. 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

    Google Scholar 

  9. 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

    Google Scholar 

  10. Tang M (2009) Gateways placement in backbone wireless mesh networks. Int J Commun Net Syst Sci 2(1):45–50

    Google Scholar 

  11. 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

    Google Scholar 

  12. 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

    Google Scholar 

  13. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. J Sci 220:671–680

    MathSciNet  Google Scholar 

  14. 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

    Google Scholar 

  15. Holland J (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor

    Google Scholar 

  16. 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

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shinji Sakamoto .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

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

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-6996-0_18

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6995-3

  • Online ISBN: 978-94-007-6996-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics