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Coordinated dual-homing in designing hierarchical wireless access network with a genetic algorithm based approach

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Abstract

With the growth of mobile users and the increasing deployment of wireless access network infrastructures, the issue of fault tolerance is becoming an important component of efficient wireless access network design. In this work, we study a survivable hierarchical network design problem. Given the available capacity, connectivity, and reliability at each level, the problem is to minimize overall connection cost for multiple requests such that the capacity, connectivity, and minimum survivability constraints are not violated. Our study is different than earlier research in regard to the coordination of multiple layers of access networks. The connectivity to the core network may be fully or partially dual-homed paths, or may be single-homed paths. Dual-homing schemes spanning to different levels in the network hierarchy are used if the single-homed connectivity is not enough to guarantee the minimum required survivability. We formulate the problem using mixed integer linear programming and prove the complexity class to be NP-hard. We then propose an off-line genetic algorithm based meta-heuristic. Given the complexity of the problem, simulation results demonstrate that the proposed approach is viable in designing fault-tolerant access networks with dual-homing capability.

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Notes

  1. Note that the term network availability [2–5] is related to, but different from network survivability and is beyond the scope of this paper. However, as shown by the authors in [7], network availability can also be improved when network survivability (or dependability) is provisioned.

References

  1. Cetinkaya, E., Broyles, D., Dandekar, A., Srinivasan, S., & Sterbenz, J. (2011). Modelling communication network challenges for future Internet resilience, survivability, and disruption tolerance: a simulation-based approach. Telecommunications Systems, 52, 751–753.

    Google Scholar 

  2. Varshney, U., Snow, A. P., & Malloy, A. D. (1999). Designing survivable wireless and mobile networks. In Proc. of IEEE wireless comm. and networking conference, New Orleans, LA, Sep. 1999 (Vol. 1, pp. 30–34).

    Google Scholar 

  3. Snow, A., Varshney, U., & Malloy, A. (2000). Reliability and survivability of wireless and mobile networks. Computer, 33(7), 49–55.

    Article  Google Scholar 

  4. American national standard T1.523-2001, Telecom glossary (2000). Alliance for telecommunications industry solutions, Feb. 2001.

  5. Varshney, U., Snow, A. P., & Malloy, A. D. (2001). Measuring the reliability and survivability of infrastructure-oriented wireless networks. In Proc. of 26th IEEE conf. on local computer networks (pp. 611–618).

    Google Scholar 

  6. Sterbenz, J., Krishnan, R., Hain, R., Jackson, A., Levin, D., Ramanathan, R., & Zao, J. (2002). Survivable mobile wireless networks: issues, challenges, and research directions. In ACM workshop on wireless security (WiSe), Atlanta, Sep. 2002.

    Google Scholar 

  7. Varshney, U., & Malloy, A. D. (2006). Multilevel fault tolerance in infrastructure-oriented wireless networks: framework and performance evaluation. International Journal of Network Management, 16(5), 351–374.

    Article  Google Scholar 

  8. Kubat, P., Smith, J. M., & Yum, C. (2000). Design of cellular networks with diversity and capacity constraints. IEEE Transactions on Reliability, 49(2), 293–303.

    Article  Google Scholar 

  9. Stavroulakis, P. (2003). Reliability, survivability and quality of large scale telecommunication systems: case study: olympic games. London: Wiley.

    Google Scholar 

  10. Gelenbe, E., Kammerman, P., & Lam, T. (1999). Performance considerations in totally mobile wireless Performance evaluation, 36–37, 387–399.

    Article  Google Scholar 

  11. Lin, Y.-B., & Pang, A.-C. (2000). Comparing soft and hard handoffs. IEEE Transactions on Vehicular Technology, 49(3), 792–798.

    Article  Google Scholar 

  12. Tipper, D., Ramaswamy, S., & Dahlberg, T. (1999). PCS network survivability. In Proc. of IEEE wireless comm. and networking conference, New Orleans, LA, Sep. 1999 (Vol. 2, pp. 1028–1032).

    Google Scholar 

  13. Tipper, D., Dahlberg, T., Shin, H., & Charnsripinyo, C. (2002). Providing fault tolerance in wireless access networks. IEEE Communications Magazine, 40(1), 58–64.

    Article  Google Scholar 

  14. Soni, S., & Pirkul, H. (2002). Design of survivable networks with connectivity requirements. Telecommunications Systems, 20(1), 133–149.

    Article  Google Scholar 

  15. Dutta, A., & Kubat, P. (1999). Design of partially survivable networks for cellular telecommunication systems. European Journal of Operational Research, 118, 52–64.

    Article  Google Scholar 

  16. Cox, L. A., & Sanchez, J. R. (2000). Designing least-cost survivable wireless backhaul networks. Joumal of Heuristics, 6, 525–540.

    Article  Google Scholar 

  17. Alevras, D., Grotschel, M., Jonas, P., Paul, U., & Wessaly, R. (1998). Survivable mobile phone network architectures: models and solution methods. IEEE Communications Magazine, 36(3), 88–93.

    Article  Google Scholar 

  18. Houéto, F., Pierre, S., Beaubrun, R., & Lemieux, Y. (2002). Reliability and cost evaluation of third-generation wireless access network topologies: a case study. IEEE Transactions on Reliability, 51(2), 229–239.

    Article  Google Scholar 

  19. Charnsripinyo, C., & Tipper, D. (2002). Designing fault tolerant wireless access networks. In Proc. of MILCOM, Oct. 2002 (Vol. 1, pp. 525–529).

    Google Scholar 

  20. Charnsripinyo, C., & Tipper, D. (2003). Topological design of survivable wireless access networks. In Proc. of DRCN, Alberta, Oct. 2003.

    Google Scholar 

  21. Charnsripinyo, C., & Tipper, D. (2005). Topological design of 3G wireless backhaul networks for service assurance. In Proc. of DRCN, Italy, Oct. 2005.

    Google Scholar 

  22. Szlovencsak, A., Godor, I., Harmatos, J., & Cinkler, T. (2002). Planning reliable UMTS terrestrial access networks. IEEE Communications Magazine, 40(1), 66–72.

    Article  Google Scholar 

  23. Vajanapoom, K., Tipper, D., & Akavipat, S. (2011). Risk based resilient network design. Telecommunications Systems, 1–13, 799–811.

    Google Scholar 

  24. Dahlberg, T. A., & Jung, J. (2001). Survivable load sharing protocols: a simulation study. Wireless Networks, 7(3), 283–296.

    Article  Google Scholar 

  25. Din, D., & Tseng, S. (2002). A genetic algorithm for solving dual-homing cell assignment problem of the two-level wireless ATM networks. Computer Communications, 25(17), 1536–1547.

    Article  Google Scholar 

  26. Huang, X., Wang, J., Vokkarane, V. M., & Jue, J. P. (2006). Fault-tolerant wireless access network design for dual-homed users. In Proc. of IEEE INFOCOM, Barcelona, Apr. 2006.

    Google Scholar 

  27. Kumar, V. (2006). Mobile database systems. New York: Wiley.

    Book  Google Scholar 

  28. Smith, C., & Meyer, J. (2005). 3G wireless with WiMAX and Wi-Fi. New York: McGraw-Hill.

    Google Scholar 

  29. Wesolowski, K. (2002). Mobile communication systems. New York: Wiley.

    Google Scholar 

  30. Daoud Yacoub, M. (2002). Wireless technology: protocols, standards, and techniques. Boca Raton: CRC Press.

    Google Scholar 

  31. Hsiao, P.-H., Hwang, A., Kung, H. T., & Vlah, D. (2001). Load-balancing routing for wireless access networks. In Proc. of IEEE INFOCOM, Anchorage, AK (Vol. 2, pp. 986–995).

    Google Scholar 

  32. Garey, M. R., & Johnson, D. S. (1979). Computers and intractability: a guide to the theory of NP-completeness. New York: Freeman

    Google Scholar 

  33. Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2001). Introduction to algorithms (2nd ed.). Cambridge: MIT Press/McGraw-Hill.

    Google Scholar 

  34. Jang, K.-W. (2011). A tabu search algorithm for routing optimization in mobile ad-hoc networks. Telecommunications Systems, 51, 171–191.

    Google Scholar 

  35. Lee, C., & Koh, S. (1997). A design of the minimum cost ring-chain network with dual-homing survivability: a tabu search approach. Computers & Operations Research, 24(9), 883–897.

    Article  Google Scholar 

  36. Krishnamachari, B., & Wicker, S. B. (2000). Optimization of fixed network design in cellular systems using local search algorithms. In IEEE vehicular technology conference (pp. 1632–1638).

    Google Scholar 

  37. Davis, L. (1991). Handbook of genetic algorithms. New York: Van Nostrand-Reinhold.

    Google Scholar 

  38. Reeves, C. R., & Rowe, J. E. (2003). Genetic algorithms—principles and perspectives: a guide to GA theory. Boston: Kluwer Academic.

    Google Scholar 

  39. Haupt, R. L., & Haupt, S. E. (2004). Practical genetic algorithms (2nd ed.). New Jersey: Wiley.

    Google Scholar 

  40. Whitley, D. (1989). The GENITOR algorithm and selection pressure: why rank-based allocation of reproductive trials is best. In Proc. of the 3rd int. conf. on genetic algorithms (pp. 116–121).

    Google Scholar 

  41. Bäck, T., & Hoffmeister, F. (1991). Extended selection mechanisms in genetic algorithms. In Proc. of the 4th int. conf. on genetic algorithms (pp. 92–99).

    Google Scholar 

  42. Srinivas, M., & Patnaik, L. M. (1994). Genetic algorithms: a survey. Computer, 27(6), 17–26.

    Article  Google Scholar 

  43. Vasconcelos, J. A., Ramírez, J. A., Takahashi, R. H. C., & Saldanha, R. R. (2001). Improvements in genetic algorithms. IEEE Transactions on Magnetics, 37(5), 3414–3417.

    Article  Google Scholar 

  44. Luke, S., & Spector, L. (1998). A revised comparison of crossover and mutation in genetic programming. In Proc. of the third annual conf. on genetic programming, Madison, WI.

    Google Scholar 

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Acknowledgements

This work has been supported in part by the National Science Foundation (NSF) under grant numbers CNS-0435105 and ANI-0133899. A preliminary and partial presentation of this study has appeared in IEEE Globecom conference, CA, November 2006.

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Authors and Affiliations

  1. Dept. of Mathematics and Computer Science, Elizabeth City State University, Elizabeth, NC, 27909, USA

    Mohammad M. Hasan

  2. Citrix Systems, Inc., 851 West Cypress Creek Road, Fort Lauderdale, FL, 33309, USA

    Xiaodong Huang

  3. Dept. of Computer Science, The University of Texas at Dallas, Richardson, TX, 75083, USA

    Jason P. Jue

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  1. Mohammad M. Hasan
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Correspondence to Mohammad M. Hasan.

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Hasan, M.M., Huang, X. & Jue, J.P. Coordinated dual-homing in designing hierarchical wireless access network with a genetic algorithm based approach. Telecommun Syst 54, 417–431 (2013). https://doi.org/10.1007/s11235-013-9741-y

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