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Weighted Steiner Connected Dominating Set and its Application to Multicast Routing in Wireless MANETs

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Abstract

In this paper, we first propose three centralized learning automata-based heuristic algorithms for approximating a near optimal solution to the minimum weight Steiner connected dominating set (WSCDS) problem. Finding the Steiner connected dominating set of the network graph is a promising approach for multicast routing in wireless ad-hoc networks. Therefore, we present a distributed implementation of the last approximation algorithm proposed in this paper (Algorithm III) for multicast routing in wireless mobile ad-hoc networks. The proposed WSCDS algorithms are compared with the well-known existing algorithms and the obtained results show that Algorithm III outperforms the others both in terms of the dominating set size and running time. Our simulation experiments also show the superiority of the proposed multicast routing algorithm over the best previous methods in terms of the packet delivery ratio, multicast route lifetime, and end-to-end delay.

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References

  1. Nadeem T., Parthasarathy S. (2006) Mobility control for throughput maximization in ad-hoc networks. Wireless Communication and Mobile Computing 6: 951–967

    Article  Google Scholar 

  2. Guha S., Khuller S. (1998) Approximation algorithms for connected dominating Sets. Algorithmica 20(4): 374–387

    Article  MathSciNet  MATH  Google Scholar 

  3. Wu, Y., Xu, Y., Chen, G., & Wang, K. (2004). On the construction of virtual multicast backbone for wireless ad-hoc networks. In IEEE international conference on mobile ad-hoc and sensor systems, pp. 294 –303.

  4. Lim H., Kim C. (2001) Flooding in wireless ad-hoc networks. Journal of Computer Communications 24: 353–363

    Article  Google Scholar 

  5. Robins, G., & Zelikovsky, A. (2000). Improved steiner tree approximation in graphs. In Proceedings of the 11th annual ACM-SIAM symposium on discrete algorithms, pp. 770–779.

  6. Singh, G., & Vellanki, K. (1998). A distributed protocol for constructing multicast trees. In Proceedings of the international conference on principles of distributed systems, France.

  7. Muhammad, R. B. (2006). Distributed steiner tree algorithm and its application in ad-hoc wireless networks. In Proceedings of the 2006 international conference on wireless networks (ICWN’06), USA, pp. 173–178.

  8. Muhammad R. B. (2007) A distributed graph algorithm for geometric routing in ad-hoc wireless networks. Journal of Networks 2(6): 50–57

    Article  Google Scholar 

  9. Aggarwal D., Dubey C. K., Mehta S. K. (2006) Algorithms on Graphs with Small Dominating Targets. ISAAC 4288: 141–152 LNCS

    MathSciNet  Google Scholar 

  10. Lee, S. J., Gerla, M., & Chiang, C. C. (1999). On-demand multicast routing protocol. In Proceedings of IEEE WCNC’99, pp. 1298–1302. New Orleans, LA.

  11. Chiang C. C., Gerla M., Zhang L. (1998) Forwarding group multicast protocol (FGMP) for multihop, mobile wireless networks. Journal of Cluster Computing 1(2): 187–196

    Article  Google Scholar 

  12. 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 

  13. An B., Papavassiliou S. (2003) MHMR: Mobility-based hybrid multicast routing protocol in mobile ad-hoc wireless networks. Wireless Communication and Mobile Computing 3: 255–270

    Article  Google Scholar 

  14. Guo S., Yang O. (2008) Maximizing multicast communication lifetime in wireless mobile ad-hoc networks. IEEE Transactions on Vehicular Technology 57: 2414–2425

    Article  MathSciNet  Google Scholar 

  15. Haleem, M., & Chandramouli, R. (2005). Adaptive downlink scheduling and rate selection: A cross layer design, special issue on mobile computing and networking. IEEE Journal on Selected Areas in Communications, 23(6).

  16. Nicopolitidis P., Papadimitriou G. I., Pomportsis A. S. (2006) Exploiting locality of demand to improve the performance of wireless data broadcasting. IEEE Transactions on Vehicular Technology 55(4): 1347–1361

    Article  Google Scholar 

  17. Nicopolitidis P., Papadimitriou G. I., Pomportsis A. S. (2003) Learning-automata-based polling protocols for wireless LANs. IEEE Transactions on Communications 51(3): 453–463

    Article  Google Scholar 

  18. Nicopolitidis P., Papadimitriou G. I., Pomportsis A. S. (2004) Distributed protocols for ad-hoc wireless LANs: A learning-automata-based approach. Ad-Hoc Networks 2(4): 419–431

    Article  Google Scholar 

  19. Nicopolitidis, P., Papadimitriou, G.I., Obaidat, M. S., & Pomportsis, A. S. (2005). Carrier-sense-assisted Adaptive Learning MAC Protocol for Distributed Wireless LANs. International Journal of Communication Systems, Wiley 18(7), 657–669.

    Google Scholar 

  20. Ramana, B. V., & Murthy, C. S. R. (2005). Learning-TCP: A novel learning automata based congestion window updating mechanism for ad-hoc wireless networks. In 12th IEEE International Conference on High 13 Performance Computing, pp. 454–464.

  21. Beigy, H., & Meybodi, M. R. (2008). Learning automata-based Dynamic guard channel algorithms. In Journal of High Speed Networks, (to appear).

  22. Beigy H., Meybodi M. R. (2005) A general call admission policy for next generation wireless networks. Computer Communications 28: 1798–1813

    Article  Google Scholar 

  23. Beigy H., Meybodi M. R. (2005) An adaptive call admission algorithm for cellular networks. Computers and Electrical Engineering 31: 132–151

    Article  MATH  Google Scholar 

  24. Beigy, H., & Meybodi, M. R. (2002). A learning automata-based dynamic guard channel scheme. In Lecture notes on information and communication technology vol. 2510, pp. 643–650. Springer.

  25. Akbari Torkestani, J., & Meybodi, M. R. (2010). An efficient cluster-based CDMA/TDMA scheme for wireless mobile ad-hoc networks: A learning automata approach. Journal of Network and Computer applications, (in press).

  26. Akbari Torkestani, J., & Meybodi, M. R. (2010). An intelligent backbone formation algorithm for wireless ad-hoc networks based on distributed learning automata. Computer Networks, Elsevier Publishing Company, (in press).

  27. Akbari Torkestani J., Meybodi M.R. (2010) Mobility-based multicast routing algorithm in wireless mobile ad-hoc networks: A learning automata approach. Journal of Computer Communications 33: 721–735

    Article  MathSciNet  Google Scholar 

  28. Wu J., Dai F., Gao M., Stojmenovic I. (2002) On calculating power-aware connected dominating sets for efficient routing in ad-hoc wireless networks. Journal of Communications and Networks 4(1): 1–12

    Google Scholar 

  29. Wu, J., & Li, H. (1999). On calculating connected dominating set for efficient routing in ad-hoc wireless networks. In Proceedings of the 3rd international workshop on discrete algorithms and methods for mobile computing and communication, pp. 7–14.

  30. Wang, Y., Wang, W., & Li, X.-Y. (2005). Distributed low-cost backbone formation for wireless ad-hoc networks. In Proceedings of the sixth ACM international symposium on mobile ad-hoc networking and computing (MobiHoc 2005), pp. 2–13.

  31. Han B. (2009) Zone-based virtual backbone formation in wireless ad-hoc networks. Ad-Hoc Networks 7: 183–200

    Article  Google Scholar 

  32. Alzoubi K. M., Wan P. -J., Frieder O. (2003) Maximal independent set, weakly connected dominating set, and induced spanners for mobile ad-hoc networks. International Journal of Foundations of Computer Science 14(2): 287–303

    Article  MathSciNet  MATH  Google Scholar 

  33. Clark B. N., Colbourn C. J., Johnson D. S. (1990) Unit Disk Graphs. Discrete Mathematics 86: 165–177

    Article  MathSciNet  MATH  Google Scholar 

  34. Marathe M. V., Breu H., Hunt H. B., Ravi S. S., Rosenkrantz D. J. (1995) Simple Heuristics for Unit Disk Graphs. Networks 25: 59–68

    Article  MathSciNet  MATH  Google Scholar 

  35. Chen, Y. Z., & Listman, A. L. (2002). Approximating minimum size weakly connected dominating sets for clustering mobile ad-hoc networks. In Proceedings of the third ACM international symposium on mobile ad-hoc networking and computing (MobiHoc’2002), pp. 157–164.

  36. Torkestani, J. A., & Meybodi, M. R. (2009). Approximating the minimum connected dominating set in stochastic graphs based on learning automata. In Proceedings of international conference on information management and engineering (ICIME 2009), pp. 672–676. Malaysia.

  37. Narendra K. S., Thathachar K. S. (1989) Learning automata: An introduction. Printice-Hall, New York

    Google Scholar 

  38. Thathachar M. A. L., Sastry P. S. (1997) A hierarchical system of learning automata that can learn the globally optimal path. Information Science 42: 743–766

    MathSciNet  Google Scholar 

  39. Thathachar M. A. L., Harita B. R. (1987) Learning automata with changing number of actions. IEEE Transactions on Systems, Man, and Cybernetics SMG17: 1095–1100

    Google Scholar 

  40. Thathachar M. A. L., Phansalkar V. V. (1995) Convergence of teams and hierarchies of learning automata in connectionist systems. IEEE Transactions on Systems, Man, and Cybernetics 24: 1459–1469

    Article  MathSciNet  Google Scholar 

  41. Lakshmivarahan S., Thathachar M. A. L. (1995) Bounds on the convergence probabilities of learning automata. IEEE Transactions on Systems, Man, and Cybernetics SMC-6: 756–763

    MathSciNet  Google Scholar 

  42. Narendra K. S., Thathachar M. A. L. (1980) On the behavior of a learning automaton in a changing environment with application to telephone traffic routing. IEEE Transactions on Systems, Man, and Cybernetics SMC-l0(5): 262–269

    Article  Google Scholar 

  43. Torkestani, J. A., & Meybodi, M. R. (2009). Solving the minimum spanning tree problem in stochastic graphs using learning automata. In Proceedings of international conference on information management and engineering (ICIME 2009). pp. 643–647. Malaysia.

  44. IEEE Computer Society LAN MAN Standards Committee, Wireless LAN Medium Access Protocol (MAC) and Physical Layer (PHY) specification, IEEE Standard 802.11-1997, The Institute of Electrical and Electronics Engineers, New York (1997).

  45. Akbari Torkestani, J., & Meybodi, M. R. (2010). Clustering the wireless ad-hoc networks: A distributed learning automata approach. Journal of Parallel and Distributed Computing, Elsevier Publishing Company (in press).

  46. Akbari Torkestani, J., & Meybodi, M. R. (2010). A new vertex coloring algorithm based on variable action-set learning automata. Journal of Computing and Informatics (in press).

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Torkestani, J.A., Meybodi, M.R. Weighted Steiner Connected Dominating Set and its Application to Multicast Routing in Wireless MANETs. Wireless Pers Commun 60, 145–169 (2011). https://doi.org/10.1007/s11277-010-9936-4

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