Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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A Measurement-Based Adaptive Control Mechanism for Pricing in Telecommunication Networks

  • Davoli, Franco (Department of Communications, Computer, and Systems Science, University of Genova) ;
  • Marchese, Mario (Department of Communications, Computer, and Systems Science, University of Genova) ;
  • Mongelli, Maurizio (Department of Communications, Computer, and Systems Science, University of Genova)
  • Received : 2008.05.21
  • Accepted : 2009.11.16
  • Published : 2010.06.30
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Abstract

The problem of pricing for a telecommunication network is investigated with respect to the users' sensitivity to the pricing structure. A functional optimization problem is formulated, in order to compute price reallocations as functions of data collected in real time during the network evolution. No a-priori knowledge about the users' utility functions and the traffic demands is required, since adaptive reactions to the network conditions are sought in real time. To this aim, a neural approximation technique is studied to exploit an optimal pricing control law, able to counteract traffic changes with a small on-line computational effort. Owing to the generality of the mathematical framework under investigation, our control methodology can be generalized for other decision variables and cost functionals.

Keywords

References

  1. C. Courcoubetis and R. Weber, Pricing Communication Networks - Economics, Technology and Modelling, John Wiley & Sons, San Francisco, CA, 2003.
  2. F.P. Kelly, A.K. Maulloo, and D.K.H. Tan, "Rate control for communication networks: Shadow prices, proportional fairness, and stability," J. Operat. Res. Soc., vol. 49, no. 3, pp. 237–252, 1998.
  3. S.H. Low and D.E. Lapsley, "Optimization flow control, I: Basic algorithm and convergence," IEEE/ACM Trans. Netw., vol. 7, no. 6, pp. 861–874, Dec. 1999. https://doi.org/10.1109/90.811451
  4. I. Paschalidis and Y. Liu, "Pricing in multiservice loss networks: Static pricing, asymptotic optimality, and demand substitution effects," IEEE/ACM Trans. Netw., vol. 10, pp. 425–437, June 2002. https://doi.org/10.1109/TNET.2002.1012372
  5. Q. Wang and J. M. Peha, "State-dependent pricing and its economic implications," Telecommun. Syst., vol. 18, pp. 315–329, 2001. https://doi.org/10.1023/A:1016730011188
  6. U. Savagaonkar, E. K. P. Chong, and R. L. Givan, "Online pricing for bandwidth provisioning in multi-class networks," Computer Netw., vol. 44, no. 6, pp. 835–853, Apr. 2004. https://doi.org/10.1016/j.comnet.2003.12.011
  7. S. Kalyanasundaram, E. K. P. Chong, and N. B. Shroff, "Optimal resource allocation in multi-class networks with user-specified utility functions," Computer Netw., vol. 38, no. 5, pp. 613–630, Apr. 2002. https://doi.org/10.1016/S1389-1286(01)00275-4
  8. N. J. Keon and G. Anandalingam, "Optimal pricing for multiple services in telecommunications networks offering quality-of-service guarantees," IEEE/ACM Trans. Netw., vol. 11, no. 1, pp. 60–80, Feb. 2003.
  9. M. Aldebert, M. Ivaldi, and C. Roucolle, "Telecommunications demand and pricing structure: An econometric analysis," Telecommun. Syst., vol. 25, pp. 89–115, 2004. https://doi.org/10.1023/B:TELS.0000011198.50511.a4
  10. L. A. Cox, "Data mining and causal modeling of customer behaviors," Telecommun. Syst., vol. 21, pp. 349–381, 2002. https://doi.org/10.1023/A:1020911018130
  11. R. Edell and P. Varaiya, "Demand for quality-differentiated network services," in Proc. CDC, San Diego, USA, Dec. 1997.
  12. M. Baglietto, R. Bolla, F. Davoli, M. Marchese, and M. Mongelli "A proposal of new price-based call admission control rules for guaranteed performance services multiplexed with best effort traffic," Comp. Commun., vol. 26, no. 13, pp. 1470–1483, 2003. https://doi.org/10.1016/S0140-3664(03)00032-X
  13. L. Badia, M. Lindstrom, J. Zander, and M. Zorzi "Demand and pricing effects on the radio resource allocation multimedia communication systems," in Proc. IEEE Globecom, San Francisco, CA, Dec. 2003, pp. 139– 143.
  14. I. C. Paschalidis and J. N. Tsitsiklis, "Congestion-dependent pricing of network services," IEEE/ACM Trans. Netw., vol. 8, pp. 171–184, Apr. 2000. https://doi.org/10.1109/90.842140
  15. X. Lin and N. B. Shroff, "Pricing-based control of large networks," in Proc. IWDC, Taormina, Italy, Sept. 2001, pp. 212–231.
  16. W.-S. Kim, "Price-based quality-of-service control framework for twoclass network services," J. Commun. and Netw., vol. 9, no. 3, Sept. 2007, pp. 319–329. https://doi.org/10.1109/JCN.2007.6182859
  17. P. Xu, M. Devetsikiotis, and G. Michailidis, "Profit-oriented resource allocation using online scheduling in flexible heterogeneous networks," Telecommun. Syst., vol. 31, no. 2–3, pp 289–303, 2006. https://doi.org/10.1007/s11235-006-6525-7
  18. K. Ross, Multiservice Loss models for Broadband Telecommunication Networks. Springer Verlag, Berlin, 1995.
  19. S. H. Low, F. Paganini, and J. C. Doyle, "Internet congestion control," IEEE Contr. Syst. Mag., vol. 22, no. 1, pp. 28–43, Feb. 2002. https://doi.org/10.1109/37.980245
  20. E. Altman, D. Artiges, and K. Traore, "On the integration of bestEffort and Guaranteed Performance Services," Europ. Trans. Telecommun., vol. 2, no. 2, Feb.–Mar. 1999.
  21. P. Marbach, O. Mihatsch, and J. N. Tsitsiklis, "Call admission control and routing in integrated services networks using neuro-dynamic programming," IEEE J. Select. Areas Commun., vol. 18, no. 2, pp. 197–208, Feb. 2000. https://doi.org/10.1109/49.824797
  22. J. H. Lepler and K. Neuhoff, "Resource reservation with a market-based protocol: What prices to expect?," Comp. Commun., vol. 26, pp. 1434– 1444, 2003. https://doi.org/10.1016/S0140-3664(03)00029-X
  23. InvisibleHand Networks, Inc. [Online]. Available: http://www.invisible hand.net
  24. N. Semret and A. Lazar, "System and method for performing a progressive second price auction technique," US Patent no. 7,177,832, Feb. 2007.
  25. O. Regev and N. Nisan, "The POPCORN market-an online market for computational resources," in Proc ACM ICE, Charleston, SC, USA, Oct. 1998.
  26. Oltsik J. Web services meet the network. IBM White paper. [Online]. Available: https://www14.software.ibm.com
  27. Cisco AON: A network embedded intelligent message routing system. Cisco Systems. [Online]. Available: http://www.cisco.com
  28. M. Poikselka, G. Mayer, H. Khartabil, and A. Niemi, The IMS IP Multimedia Concepts and Services, 2nd ed. JohnWiley & Sons, LTD, Hoboken, June 2007.
  29. E. W. Fulp and D. S. Reeves, "Bandwidth provisioning and pricing for networks with multiple classes of service," Computer Netw., vol. 46, no. 1, pp. 41–52, 2004. https://doi.org/10.1016/j.comnet.2004.03.018
  30. F. Davoli, M. Marchese, and M. Mongelli, "Neural decision making for decentralized pricing-based call admission control," in Proc. IEEE ICC, Seoul, Korea, May 2005, pp. 16–20.
  31. R. Zoppoli, M. Sanguineti, and T. Parisini, "Approximating networks and extended Ritz method for solution of functional optimization problems," J. Optim. Theory and Applic., vol. 112, no. 2, pp. 403–439, Feb. 2002. https://doi.org/10.1023/A:1013662124879
  32. M. Baglietto, T. Parisini, and R. Zoppoli, "Distributed-information neural control: The case of dynamic routing in traffic networks," IEEE Trans. Neural Netw., vol. 12, no. 3, pp. 485–502, May 2001. https://doi.org/10.1109/72.925553
  33. S. Chong, S. Li, and J. Ghosh, "Predictive dynamic bandwidth allocation for efficient transport of real-time VBR video over ATM," IEEE J. Sel. Areas Commun., vol. 13, no. 1, pp. 12–23, Jan. 1995. https://doi.org/10.1109/49.363150
  34. [Online]. Available: http://www.bgp-qos.org/forum/
  35. S. Lanning, D. Mitra, Q. Wang, and M. Wright, "Optimal planning for optical transport networks," Phil. Trans. Royal Soc. London A, vol. 358, no. 1773, pp. 2183–2196, Aug. 2000. https://doi.org/10.1098/rsta.2000.0640
  36. (1998, Feb.). CFSQP Version 2.5d-Released. [Online]. Available: http://www.isr.umd.edu/Labs/CACSE/FSQP