Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Analysis of Inter-Domain Collaborative Routing: Provider Competition for Clients

  • Nicholes, Martin O (Department of Electrical and Computer Engineering, University of California) ;
  • Chuah, Chen-Nee (Department of Electrical and Computer Engineering, University of California) ;
  • Wu, Shyhtsun Felix (Department of Computer Science, University of California) ;
  • Mukherjee, Biswanath (Department of Computer Science, University of California)
  • Received : 2010.06.25
  • Accepted : 2011.06.28
  • Published : 2011.10.31
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Abstract

Any server offering a routing service in the Internet would naturally be in competition for clients, and clients may need to utilize service from a specific server in order to achieve a desired result. We study the various properties of this competition, such as the fraction of route requests handled by a routing service provider and the fraction of total revenue obtained. As the routing service providers (i.e., servers or routers in this context) compete, they may alter behavior in order to optimize one of the above properties. For example, a service provider may lower the price charged for its service, in order to increase the number of clients served. Our models are based on servers offering a routing service to clients within representative network topologies based on actual Internet sub-graphs. These models provide, a framework for evaluating competition in the Internet. We monitor key aspects of the service, as several variables are introduced into the models. The first variable is the fraction of client requests that will pay more for a better quality route. The remaining requests are normal client requests that are satisfied by the most economical route. The second variable is the fraction of servers who choose to lower service prices in order to maximize the number of client requests served. As this fraction increases, it is more likely that a server will lower the price. Finally, there are some resource constraints applied to the model, to increase the difficulty in providing a routing solution, i.e., to simulate a realistic scenario. We seek to understand the effect on the overall network, as service providers compete. In simple cases, we show that this competition could have a negative impact on the overall efficiency of a service. We show that the routing variety present in the larger models is unable to mask this tendency and the routing service performance is decreased due to competition.

Keywords

References

  1. M. Nicholes, "Network security in the core Internet," Ph.D. dissertation, University of California, Davis, 2009,
  2. E. Rasmusen, Games and Information: an Introduction to Game Theory, Basil Blackwell Inc., 1989.
  3. F.-N. Pavlidou and K. Koltsidas, "Game theory for routing modeling in communication networks-a survey," J. Commun. Netw., vol. 10, no. 3, pp. 268-287, 2008. https://doi.org/10.1109/JCN.2008.6388348
  4. A. Orda, R. Rom, and N, Shimkin, "Competitive routing in multiuser communication networks," IEEE/ACM Trans. Netw., vol. 1, no. 5, pp. 510-521, 1993, https://doi.org/10.1109/90.251910
  5. R. Cocchi, S. Shenker, D. Estrin, and L. Zhang, "Pricing in computer networks: Motivation, formulation, and example," IEEE/ACM Trans. Netw., vol. 1, no. 6, pp. 614-627, 1993, https://doi.org/10.1109/90.266050
  6. X. Cao, H. Shen, R. Milito, and P. Wirth, "Internet pricing with a game theoretical approach: Concepts and examples," IEEE/ACM Trans. Netw., vol. 10, no. 2, pp. 208-216, 2002. https://doi.org/10.1109/90.993302
  7. R. La and V. Anantharam, "Optimal routing control: Repeated game approach," IEEE Trans. Autom. Control, vol. 47, no. 3, pp. 437-450, 2002, https://doi.org/10.1109/9.989076
  8. K. Loja, J. Szigeti, and T. Cinkler, "Inter-domain routing in multiprovider optical networks: Game theory and simulations," Next Generation Internet Netw., pp. 157-164, 2005.
  9. L. Li and C. Chen, "Exploring possible strategies for competitions between autonomous systems," in Proc. IEEE ICC, 2008.
  10. Y. Xi and E. Yeh, "Pricing, competition, and routing for selfish and strategic nodes in multi-hop relay networks," in Proc. IEEE INFOCOM, 2008.
  11. S. Shelford, G. Shoja, and E. Manning, "Achieving optimal revenues in dynamically priced network services with QoS guarantees," Comput, Netw., vol. 51, no. 11, pp, 3294-3304, 2007. https://doi.org/10.1016/j.comnet.2007.01.021
  12. R. D. McKelvey, A. M. McLennan, and T. L. Turocy. (2007). Gambit: Software tools for game theory, Version 0.2007.01.30. [Online]. Available: http://www.gambit-project.org
  13. J. Cowie, A. Ogielski, and D. Nicol. (2002). The SSFNet network simulator. [Online]. Available: http://www.ssfnet.org/homePage.html
  14. B. Premore. (2000). Multi-AS topologies from BGP routing tables. [Online]. Available: http://www.ssfnet.org/Exchange/gallery/asgraph/src.tar.gz
  15. W. Xu and J. Rexford, "MIRO: Multi-path interdomain routing," ACM SIGCOMM Comput. Commun. Review, vol. 36, no. 4, pp, 171-182, 2006, https://doi.org/10.1145/1151659.1159934