Skip to main content
SpringerLink
Log in

A stable virtual backbone for wireless MANETS

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

Due to the highly dynamicity and absence of a fixed infrastructure in wireless mobile ad hoc networks (MANET), formation of a stable virtual backbone through which all the network hosts are connected is of great importance. In this paper, a learning automata-based distributed algorithm is proposed for constructing the most stable virtual backbone of the MANET. To do so, the backbone formation problem is first modeled by the stochastic version of the bounded diameter minimum spanning tree (BDMST) problem. Then, the network backbone is constructed by solving the stochastic BDMST problem for the network topology graph. Several simulation experiments are conducted to investigate the efficiency of the proposed backbone formation protocol. The obtained results are compared with those of the best existing methods. Numerical results show the superiority of the proposed method over the others in terms of backbone lifetime, end-to-end delay, backbone size, packet delivery ratio, and control message overhead.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Basagni, S., Conti, M., Giordano, S., & Stojmenovic, I. (2004). Mobile ad hoc networking. New York: IEEE Press.

    Book  Google Scholar 

  2. Mohapatra, P., & Krishnamurthy, S. (2005). Ad hoc networks: technologies and protocols. Berlin: Springer.

    Book  Google Scholar 

  3. Li, Y., Thai, M. T., Wang, F., Yi, C. W., Wang, P. J., & Du, D. Z. (2005). On greedy construction of connected dominating sets in wireless networks. Wireless Communications and Mobile Computing. Special issue.

  4. Alzoubi, K. M., Li, X. Y., Wang, Y., Wan, P. J., & Frieder, O. (2003). Geometric spanners for wireless ad hoc network. IEEE Transactions on Parallel and Distributed Systems, 14(4), 408–421.

    Article  Google Scholar 

  5. Dai, F., & Wu, J. (2004). An extended localized algorithm for connected dominating set formation in ad hoc wireless networks. IEEE Transactions on Parallel and Distributed Systems, 15(10), 908–920.

    Article  Google Scholar 

  6. Butenko, S., Cheng, X., Oliveira, C., & Pardalos, P. M. (2004). A new heuristic for the minimum connected dominating set problem on ad hoc wireless networks. In Recent developments in cooperative control and optimization (pp. 61–73). Dordrecht: Kluwer Academic.

    Chapter  Google Scholar 

  7. Cheng, X., Ding, M., Hongwei, D., & Jia, X. (2006). Virtual backbone construction in multihop ad hoc wireless networks. International Journal of Wireless Communications and Mobile Computing, 6, 183–190.

    Article  Google Scholar 

  8. Al-Karaki, J. N., & Kamal, A. E. (2008). Efficient virtual-backbone routing in mobile ad hoc networks. Computer Networks, 52, 327–350.

    Article  Google Scholar 

  9. Smys, S., & Josemin Bala, G. (2011). Efficient self-organized backbone formation in mobile ad hoc networks (MANETs). Computers & Electrical Engineering. doi:10.1016/j.compeleceng.2011.03.006.

    Google Scholar 

  10. Hökelek, I., Uyar, M. Ü., & Fecko, M. A. (2008). On stability analysis of virtual backbone in mobile ad hoc networks. Wireless Networks, 14, 87–102.

    Article  Google Scholar 

  11. Lin, Z., Xu, L., Wang, D., & Gao, J. (2006). A coloring based backbone construction algorithm in wireless ad hoc network. In Lecture notes in computer science (Vol. 3947, pp. 509–516). Berlin: Springer.

    Google Scholar 

  12. Dagdeviren, O., & Erciyes, K. (2006). A distributed backbone formation algorithm for mobile ad hoc networks. In Lecture notes in computer science (Vol. 4330, pp. 219–230). Berlin: Springer.

    Google Scholar 

  13. Paul, B., Rao, S. V., & Nandi, S. (2005). An efficient distributed algorithm for finding virtual backbones in wireless ad-hoc networks. In Lecture notes in computer science (Vol. 3769, pp. 302–311). Berlin: Springer.

    Google Scholar 

  14. Li, V., Park, H. S., & Oh, H. (2006). A cluster-label-based mechanism for backbones on mobile ad hoc networks. In Lecture notes in computer science (Vol. 3970, pp. 26–36). Berlin: Springer.

    Google Scholar 

  15. Akbari Torkestani, J., & Meybodi, M. R. (2010). An intelligent backbone formation algorithm in wireless ad hoc networks based on distributed learning automata. Journal of Computer Networks, 54(5), 826–843.

    Article  Google Scholar 

  16. Akbari Torkestani, J. (2012). A new approach to the job scheduling problem in computational grids. Cluster Computing, 15(3), 201–210.

    Article  Google Scholar 

  17. Akbari Torkestani, J. (2012). Degree-constrained minimum spanning tree problem in stochastic graph. Cybernetics and Systems, 43(1), 1–21.

    Article  Google Scholar 

  18. Raymond, K. (1989). A tree-based algorithm for distributed mutual exclusion. ACM Transactions on Computer Systems, 7(1), 61–77.

    Article  Google Scholar 

  19. Bookstein, A., & Klein, S. T. (2001). Compression of correlated bitvectors. Information Systems, 16, 110–118.

    Google Scholar 

  20. Achuthan, N. R., Caccetta, L., Caccetta, P., & Geelen, A. (1994). Computational methods for the diameter restricted minimum weight spanning tree problem. Australasian Journal of Combinatorics, 10, 51–71.

    Google Scholar 

  21. Gruber, M., & Raidl, G. R. (2005). A new 0-1 ILP approach for the bounded diameter minimum spanning tree problem. In Proceedings of the 2nd international network optimization conference.

    Google Scholar 

  22. Aggarwal, V., Aneja, Y., & Nair, K. (1982). Minimal spanning tree subject to a side constraint. Computers & Operations Research, 9, 287–296.

    Article  Google Scholar 

  23. Abdalla, A., Deo, N., & Gupta, P. (2000). Random-tree diameter and the diameter constrained MST. Congressus Numerantium, 144, 161–182.

    Google Scholar 

  24. Prim, R. C. (1957). Shortest connection networks and some generalizations. The Bell System Technical Journal, 36, 1389–1401.

    Article  Google Scholar 

  25. Raidl, G. R., & Julstrom, B. A. (2003). Greedy heuristics and an evolutionary algorithm for the bounded-diameter minimum spanning tree problem. In Proceedings of the 2003 ACM symposium on applied computing (pp. 747–752).

    Chapter  Google Scholar 

  26. Julstrom, B. A. (2004). Encoding bounded diameter minimum spanning trees with permutations and random keys. In Proceedings of genetic and evolutionary computational conference (GECCO’2004).

    Google Scholar 

  27. Julstrom, B. A., & Raidl, G. R. (2003). A permutation-coded evolutionary algorithm for the bounded diameter minimum spanning tree problem. In Genetic and evolutionary computation conferences workshops proceedings, workshop on analysis and design of representations (pp. 2–7).

    Google Scholar 

  28. Julstrom, B. A. (2004). Encoding bounded-diameter minimum spanning trees with permutations and with random keys. In Lecture note on computer science: Vol. 3102. Proceedings of the genetic and evolutionary computation conference (pp. 1281–1282). Berlin: Springer.

    Google Scholar 

  29. Raidl, G. R., & Julstrom, B. A. (2003). Edge sets: an effective evolutionary coding of spanning trees. IEEE Transactions on Evolutionary Computation, 7(3), 225–239.

    Article  Google Scholar 

  30. Singh, A., & Gupta, A. K. (2007). Improved heuristics for the bounded-diameter minimum spanning tree problem. Soft Computing, 11(10), 911–921.

    Article  Google Scholar 

  31. Gruber, M., & Raidl, G. R. (2005). Variable neighborhood search for the bounded diameter minimum spanning tree problem. In Proceedings of the 18th mini euro conference on variable neighborhood search, Tenerife, Spain.

    Google Scholar 

  32. Binh, H., Hoai, N., & McKay, R. I. (2008). A new hybrid genetic algorithm for solving the bounded diameter minimum spanning tree problem. In Proceedings of IEEE world congress on computational intelligence (CEC’2008) (pp. 3127–3133).

    Google Scholar 

  33. Binh, H., & Nghia, N. (2009). New multiparent recombination in genetic algorithm for solving bounded diameter minimum spanning tree problem. In Proceedings of 1st Asian conference on intelligent information and database systems (pp. 283–288).

    Google Scholar 

  34. Requejo, C., & Santos, E. (2009). Greedy heuristics for the diameter-constrained minimum spanning tree problem. Journal of Mathematical Sciences, 161(6), 930–943.

    Article  Google Scholar 

  35. Feo, T. A., & Resende, M. G. C. (1989). A probabilistic heuristic for a computationally difficult set covering problem. Operations Research Letters, 8, 67–71.

    Article  Google Scholar 

  36. Lourenço, H. R., Martin, O. C., & Stutzle, T. (2002). Iterated local search. In Handbook of metaheuristics (pp. 321–353). Dordrecht: Kluwer.

    Google Scholar 

  37. Lucena, A., Ribeiro, C. C., & Santos, A. C. (2010). A hybrid heuristic for the diameter constrained minimum spanning tree problem. Journal of Global Optimization, 46, 363–381.

    Article  Google Scholar 

  38. Gruber, M., Hemert, J., & Raidl, G. R. (2006). Neighborhood searches for the bounded diameter minimum spanning tree problem embedded in a VNS, EA and ACO. In Proceedings of genetic and evolutionary computational conference (GECCO’2006).

    Google Scholar 

  39. IEEE Computer Society LAN MAN Standards Committee (1997). Wireless LAN medium access protocol (MAC) and physical layer (PHY) specification, IEEE standard 802.11-1997. New York: The Institute of Electrical and Electronics Engineers.

    Google Scholar 

  40. Ballardie, A., Francis, P., & Crowcroft, J. (1993). Core-based trees (CBT)—an architecture for scalable inter-domain multicast routing. Computer Communication Review, 23(4), 85–95.

    Article  Google Scholar 

  41. Lee, S.-J., Su, W., & Gerla, M. (2001). Wireless ad hoc multicast routing with mobility prediction. Mobile Networks and Applications, 6, 351–360.

    Article  Google Scholar 

  42. Su, W., Lee, S.-J., & Gerla, M. (2001). Mobility prediction and routing in ad hoc wireless networks. International Journal of Network Management, 11, 3–30.

    Article  Google Scholar 

  43. Leng, S., Zhang, L., Fu, H., & Yang, J. (2007). Mobility analysis of mobile hosts with random walking in ad hoc networks. Computer Networks, 51, 2514–2528.

    Article  Google Scholar 

  44. Birkan, G., & Kennington, J. (2009). Design procedures for backbone transport networks with shared protection: optimization-based models, exact and heuristic algorithms, and unavailability computations. Telecommunications Systems, 41(2), 97–120.

    Article  Google Scholar 

  45. Duresi, A., & Paruchuri, V. (2008). Adaptive backbone protocol for heterogeneous wireless networks. Telecommunications Systems, 38(3–4), 83–97.

    Article  Google Scholar 

  46. Chari, K. (1996). Multi-hour design of computer backbone networks. Telecommunications Systems, 6(1), 347–365.

    Article  Google Scholar 

  47. Wu, J., & Li, H. (2001). A dominating-set-based routing scheme in ad hoc wireless networks. Telecommunications Systems, 18(1–3), 13–36.

    Article  Google Scholar 

  48. Striki, M., & McAuley, T. (2011). Using novel distributed heuristics on hexagonal connected dominating sets to model routing dissemination. Telecommunications Systems. doi:10.1007/s11235-011-9492-6.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Arak Branch, Islamic Azad University, Arak, Iran

    Javad Akbari Torkestani

Authors
  1. Javad Akbari Torkestani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Javad Akbari Torkestani.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Akbari Torkestani, J. A stable virtual backbone for wireless MANETS. Telecommun Syst 55, 137–148 (2014). https://doi.org/10.1007/s11235-013-9760-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-013-9760-8

Keywords

Search

Navigation