Telecommunication Systems

, Volume 64, Issue 4, pp 571–584 | Cite as

Cooperation and coalitional stability in decentralized wireless networks

Article

Abstract

In this paper we consider a wireless contextualization of the local routing protocol on scale-free networks embedded in a plane and analyze on the one hand how cooperation affects network efficiency, and on the other hand the stability of cooperation structures. Cooperation is interpreted on k-cliques as local exchange of topological information between cooperating agents. Cooperative activity of nodes in the proposed model changes the routing strategy at the level of the coalition group and consequently influences the entire routing process on the network. We show that the proposed cooperation model enhances the network performance in the sense of reduced passage time and jamming. Payoff of a certain node is defined based on its energy consumption during the routing process. We show that if the payoff of the nodes is the energy saving compared to the all-singleton case, basically coalitions are not stable, since increased activity within coalition increases costs. We introduce coalitional load balancing and net reward to enhance coalitional stability and thus the more efficient operation of the network. As in the proposed model cooperation strongly affects routing dynamics of the network, externalities will arise and the game is defined in a partition function form.

Keywords

Cooperative game theory Local routing Wireless systems 

References

  1. 1.
    Abolhasan, M., Wysocki, T., & Dutkiewicz, E. (2004). A review of routing protocols for mobile ad hoc networks. Ad hoc Networks, 2(1), 1–22.CrossRefGoogle Scholar
  2. 2.
    Akkarajitsakul, K., Hossain, E., Niyato, D., & Kim, D. I. (2011). Game theoretic approaches for multiple access in wireless networks: A survey. IEEE Communications Surveys & Tutorials, 13(3), 372–395.CrossRefGoogle Scholar
  3. 3.
    Al-Kanj, L., Saad, W., Dawy, Z. (2011). A game theoretic approach for content distribution over wireless networks with mobile-to-mobile cooperation. In 2011 IEEE 22nd International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC) (pp. 1567–1572). Piscataway: IEEE.Google Scholar
  4. 4.
    Albert, R., Jeong, H., & Barabási, A. L. (1999). Internet: Diameter of the world-wide web. Nature, 401(6749), 130–131.CrossRefGoogle Scholar
  5. 5.
    Altman, E., & Wynter, L. (2004). Equilibrium, games, and pricing in transportation and telecommunication networks. Networks and Spatial Economics, 4(1), 7–21.CrossRefGoogle Scholar
  6. 6.
    Altman, E., Boulognea, T., El-Azouzi, R., Jimenez, T., & Wynter, L. (2006). A survey on networking games in telecommunications. Computers & Operations Research, 33, 286–311.CrossRefGoogle Scholar
  7. 7.
    Arenas, A., Díaz-Guilera, A., & Guimera, R. (2001). Communication in networks with hierarchical branching. Physical Review Letters, 86(14), 3196.CrossRefGoogle Scholar
  8. 8.
    Aumann, R. J., & Peleg, B. (1960). Von Neumann-Morgenstern solutions to cooperative games without side payments. Bulletin of the American Mathematical Society, 66, 173–179.CrossRefGoogle Scholar
  9. 9.
    Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.CrossRefGoogle Scholar
  10. 10.
    Barabási, A. L., Albert, R., & Jeong, H. (1999). Mean-field theory for scale-free random networks. Physica A: Statistical Mechanics and its Applications, 272(1), 173–187.CrossRefGoogle Scholar
  11. 11.
    Chander, P., & Tulkens, H. (1997). The core of and economy with multilateral environmental externalities. International Journal of Game Theory, 26(3), 379–401.CrossRefGoogle Scholar
  12. 12.
    Cohen, K., Leshem, A., & Zehavi, E. (2013). Game theoretic aspects of the multi-channel aloha protocol in cognitive radio networks. IEEE Journal on Selected Areas in Communications, 31(11), 2276–2288.CrossRefGoogle Scholar
  13. 13.
    Cominetti, R., Correa, J. R., & Stier-Moses, N. E. (2006). Network games with atomic players. Automata, languages and programming (pp. 525–536). Berlin: Springer.Google Scholar
  14. 14.
    Csercsik, D., Imre, S. (2013). Comparison of router intelligent and cooperative host intelligent algorithms in a continous model of fixed telecommunication networks. In International Conference on Telecommunications and Network Engineering, WASET (pp. 719–727).Google Scholar
  15. 15.
    Csercsik, D., Sziklai, B. (2012). Traffic routing oligopoly. Central European Journal of Operations Research, 1–20.Google Scholar
  16. 16.
    D’Hulst, R., & Rodgers, G. (2000). Exact solution of a model for crowding and information transmission in financial markets. International Journal of Theoretical and Applied Finance, 3(04), 609–616.CrossRefGoogle Scholar
  17. 17.
    Douligeris, C., & Mazumdar, R. (1992). A game theoretic perspective to flow control in telecommunication networks. Journal of the Franklin Institute, 329(2), 383–402.CrossRefGoogle Scholar
  18. 18.
    Eguiluz, V. M., & Zimmermann, M. G. (2000). Transmission of information and herd behavior: An application to financial markets. Physical Review Letters, 85(26), 5659.CrossRefGoogle Scholar
  19. 19.
    Feldmann, R., Gairing, M., Lucking, T., Monien, B., & Rode, M. (2003). Selfish routing in non-cooperative networks: A survey. In B. Rovan & P. Vojtás (Eds.), Mathematical foundations of computer science 2003 (Vol. 2747, pp. 21–45). Lecture Notes in Computer Science Berlin / Heidelberg: Springer.Google Scholar
  20. 20.
    Garg, N., Aswal, K., & Dobhal, D. C. (2012). A review of routing protocols in mobile ad hoc networks. International Journal of Information Technology, 5(1), 177–180.Google Scholar
  21. 21.
    Han, Z., Niyato, D., Saad, W., Basar, T., & Hjorungnes, A. (2012). Game theory in wireless and communication networks. Cambridge: Cambridge University Press.Google Scholar
  22. 22.
    Hong, X., Xu, K., & Gerla, M. (2002). Scalable routing protocols for mobile ad hoc networks. IEEE Network, 16(4), 11–21.CrossRefGoogle Scholar
  23. 23.
    Ibrahim, A., Han, Z., & Liu, K. R. (2008). Distributed energy-efficient cooperative routing in wireless networks. IEEE Transactions on Wireless Communications, 7(10), 3930–3941.CrossRefGoogle Scholar
  24. 24.
    Jackson, M. O. (2008). Social and Economic Networks. Princeton: Princeton University Press.Google Scholar
  25. 25.
    Johari, R., Mannor, S., & Tsitsiklis, J. (2006). A contract-based model for directed network formation. Games and Economic Behavior, 56(2), 201–224. doi:10.1016/j.geb.2005.08.010.CrossRefGoogle Scholar
  26. 26.
    Karamchandani, N., Minero, P., Franceschetti, M. (2011). Cooperation in multi-access networks via coalitional game theory. In 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton) (pp. 329–336). Piscataway: IEEE.Google Scholar
  27. 27.
    Khandani, A., Modiano, E., Abounadi, J., & Zheng, L. (2005). Cooperative routing in wireless networks. In B. Szymanski & Y. Bulent (Eds.), Advances in pervasive computing and networking (pp. 97–117). New York: Springer.CrossRefGoogle Scholar
  28. 28.
    Khandani, A., Abounadi, J., Modiano, E., & Zheng, L. (2007). Cooperative routing in static wireless networks. IEEE Transactions on Communications, 55, 2185–2192.CrossRefGoogle Scholar
  29. 29.
    Kóczy, L. Á. (2007a). A recursive core for partition function form games. Theory and Decision, 63(1), 41–51.CrossRefGoogle Scholar
  30. 30.
    Kóczy, L. Á. (2007b). A recursive core for partition function form games. Theory and Decision, 63(1), 41–51. doi:10.1007/s11238-007-9030-x.CrossRefGoogle Scholar
  31. 31.
    Kontogiannis, S., Spirakis, P. (2005). Atomic selfish routing in networks: A survey. In Internet and network economics (pp. 989–1002). Springer.Google Scholar
  32. 32.
    Manna, S. S., & Sen, P. (2002). Modulated scale-free network in euclidean space. Physical Review E, 66(6), 066,114.CrossRefGoogle Scholar
  33. 33.
    Mauve, M., Widmer, A., & Hartenstein, H. (2001). A survey on position-based routing in mobile ad hoc networks. IEEE Network, 15(6), 30–39.CrossRefGoogle Scholar
  34. 34.
    Orda, A., Rom, R., & Shimkin, N. (1993). Competitive routing in multiuser communication networks. IEEE/ACM Transactions on Networking (ToN), 1(5), 510–521.CrossRefGoogle Scholar
  35. 35.
    Pantisano, F., Bennis, M., Saad, W., Debbah, M. (2011a). Cooperative interference alignment in femtocell networks. In: 2011 IEEE Global Telecommunications Conference (GLOBECOM 2011) (pp. 1–6). Piscataway: IEEE.Google Scholar
  36. 36.
    Pantisano, F., Bennis, M., Saad, W., Verdone, R., Latva-aho, M. (2011b). Coalition formation games for femtocell interference management: A recursive core approach. In 2011 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1161–1166). Piscataway: IEEE.Google Scholar
  37. 37.
    Pantisano, F., Bennis, M., Saad, W., Debbah, M., & Latva-aho, M. (2012). Interference alignment for cooperative femtocell networks: A game-theoretic approach. IEEE Transactions on Mobile Computing.Google Scholar
  38. 38.
    Reh, F. J. (2005). Pareto’s principle-the 80–20 rule. Business Credit-New York Then Columbia MD, 107(7), 76.Google Scholar
  39. 39.
    Roughgarden, T. (2005). Selfish routing and the price of anarchy. Cambridge: MIT Press.Google Scholar
  40. 40.
    Saad, W. (2010). Coalitional game theory for distributed cooperation in next generation wireless networks. PhD thesis, University of Oslo.Google Scholar
  41. 41.
    Saad, W., Han, Z., Debbah, M., & Hjorungnes, A. (2008). A distributed merge and split algorithm for fair cooperation in wireless networks. In IEEE International Conference on Communications Workshops, 2008. ICC Workshops ’08 (pp. 311–315). DOI:10.1109/ICCW.2008.65.
  42. 42.
    Saad, W., Han, Z., Basar, T., Debbah, M., & Hjorungnes, A. (2009a). A selfish approach to coalition formation among unmanned air vehicles in wireless networks. In: International Conference on Game Theory for Networks, 2009. GameNets ’09 (pp. 259–267). DOI:10.1109/GAMENETS.2009.5137409.
  43. 43.
    Saad, W., Han, Z., Debbah, M., Hjorungnes, A., & Basar, T. (2009). Coalitional game theory for communication networks. IEEE Signal Processing Magazine, 26(5), 77–97. doi:10.1109/MSP.2009.000000.CrossRefGoogle Scholar
  44. 44.
    Saad, W., Han, Z., Debbah, M., Hjorungnes, A., & Basar, T. (2009c). Coalitional games for distributed collaborative spectrum sensing in cognitive radio networks. In INFOCOM 2009, IEEE (pp. 2114–2122). DOI:10.1109/INFCOM.2009.5062135.
  45. 45.
    Shenoy, P. P. (1979). On coalition formation: A game-theoretical approach. International Journal of Game Theory, 8(3), 133–164.CrossRefGoogle Scholar
  46. 46.
    Tadić, B., & Rodgers, G. (2002). Packet transport on scale-free networks. Advances in Complex Systems, 5(04), 445–456.CrossRefGoogle Scholar
  47. 47.
    Tadić, B., & Rodgers, G. (2010). Modelling conflicts with cluster dynamics in networks. Physica A: Statistical Mechanics and Its Applications, 389(23), 5495–5502.Google Scholar
  48. 48.
    Tadić, B., & Thurner, S. (2004). Information super-diffusion on structured networks. Physica A: Statistical Mechanics and its Applications, 332, 566–584.Google Scholar
  49. 49.
    Tadić, B., Thurner, S., & Rodgers, G. (2004). Traffic on complex networks: Towards understanding global statistical properties from microscopic density fluctuations. Physical Review E, 69(3), 036,102.CrossRefGoogle Scholar
  50. 50.
    Tadić, B., Rodgers, G., & Thurner, S. (2007). Transport on complex networks: Flow, jamming and optimization. International Journal of Bifurcation and Chaos, 17(07), 2363–2385.CrossRefGoogle Scholar
  51. 51.
    Thrall, R., & Lucas, W. (1963). \(n\)-person games in partition function form. Naval Research Logistics Quarterly, 10(4), 281–298.CrossRefGoogle Scholar
  52. 52.
    Wang, W. X., Wang, B. H., Yin, C. Y., Xie, Y. B., & Zhou, T. (2006). Traffic dynamics based on local routing protocol on a scale-free network. Physical Review E, 73(2), 026,111.CrossRefGoogle Scholar
  53. 53.
    Wang, W. X., Yin, C. Y., Yan, G., & Wang, B. H. (2006). Integrating local static and dynamic information for routing traffic. Physical Review E, 74(1), 016,101.CrossRefGoogle Scholar
  54. 54.
    Yin, C. Y., Wang, B. H., Wang, W. X., Yan, G., & Yang, H. J. (2006). Traffic dynamics based on an efficient routing strategy on scale free networks. The European Physical Journal B-Condensed Matter and Complex Systems, 49(2), 205–211.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Faculty of Information Technology and BionicsPázmány Péter Catholic UniversityBudapestHungary
  2. 2.Department of Networked Systems and ServicesBudapest University of Technology and EconomicsBudapestHungary

Personalised recommendations