Optimal Link Allocation and Revenue Maximization

  • Joutsensalo, Jyrki (Faculty of Information Technology, Department of Mathematical Information Technology, Agora, Mattilanniemi) ;
  • Hamalainen, Timo (Faculty of Information Technology, Department of Mathematical Information Technology, Agora, Mattilanniemi)
  • Published : 2002.06.01

Abstract

In this paper, the maximal capacity of the data network link has attempted to be exploited by using the dynamic allocation strategy. We propose a new methodology based on the economic models for competing traffic classes (classes of sessions) in packet networks. As the demand for network services accelerates, users' satisfaction to the service level might decrease due to the congestion at the network nodes. To prevent this, efficient allocation of a networks resources, such as available bandwidth and switch capacity, is needed. By using the so-called user profile as well as the utility (e.g., data rate) functions, it is possible to allocate data rates and other utilities using the arbitrary number of QoS classes, say $0.01,...,$10.

Keywords

References

  1. I. C. Paschalidis and J. N. Tsitsiklis, 'Congestion-dependent pricing of network services,' IEEE/ACM Trans. Networking, vol. 8, no. 2, pp. 171-183, Apr. 2000 https://doi.org/10.1109/90.842140
  2. F. Kelly , 'Charging and rate control for elastic traffic,' European Trans. Telecommun., vol. 8, pp. 33-37, 1997 https://doi.org/10.1002/ett.4460080106
  3. F. P. Kelly, A. M. Maulloo, and D. K. H. Tan, 'Rate control in communication networks: Shadow prices, Proportional fairness and stability,' J. Operational Research Society 49, 1998
  4. F. P. Kelly, 'Notes on effective bandwidths,' in Stochastic Networks'. Theory and Applications, S. Zachary, I. B. Ziedins, and E P. Kelly, Eds. London, U. K.: Oxford Univ. Press, vol. 9, pp. 141-168, 1996
  5. R. Cocchi et al., 'Pricing in computer networks: Motivation, formulation and example,' IEEE/ACM Trans. Networking, vol. 1, no. 6, pp. 614-627, Dec. 1993 https://doi.org/10.1109/90.266050
  6. R. J. Gibbens and E. P. Kelly, 'Resource pricing and the evolution of congestion control,' Automatica, vol. 35, no. 12, pp. 1969-1985, 1999 https://doi.org/10.1016/S0005-1098(99)00135-1
  7. S. Dewan and H. Mendelson, 'User delay costs and internal pricing for a service facility,' Management Science, vol. 36, no. 12, pp.1502-1517, 1990 https://doi.org/10.1287/mnsc.36.12.1502
  8. S. Whang and H. Mendelson, 'Optimal incentive-compatible priority policy for The M/M/1 Queue,' Operations Research, vol. 38, pp. 870-883, 1990 https://doi.org/10.1287/opre.38.5.870
  9. D. Bertsimas, I. Ch. Paschalidis, and J. N. Tsitsiklis, 'On the large deviations behavior of acyclic networks of G/G/1 queues,' Ann. Appl. Prob., vol. 8, no.4, pp. 1027-1069, 1998 https://doi.org/10.1214/aoap/1028903373
  10. J. K. Mackie-Mason and H. R. Varian, Pricing the internet Public Access to the Internet, Prentice-Hall, 1995
  11. A. Gubta, D. O. Stahl, and A. B. Whinston, 'A stochastic equilibrium model of internet pricing,' J. Economics Dynamics Contr., vol. 21, no.4-5, pp. 697-722, 1997 https://doi.org/10.1016/S0165-1889(96)00003-6
  12. A. M. Odlyzko, 'Paris metro pricing for the internet,' in Proc of ACM Conf. Elec. Commerce, 1999, pp. 140-147
  13. R. Gibbens, R. Mason, and R. Steinberg, 'Internet service classes under competition,' J. Selected Areas Commun., vol. 18, no. 12, pp. 2490-2498, 2000 https://doi.org/10.1109/49.898732
  14. T. M. Cover and J. A. Thomas, Elements of Information Theory, Wiley 1991
  15. J. Banks, J. S. Carson II, and B. L. Nelson, Discrete-Event System Simulation, Prentice-Hall Inc. 1996