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Virtual partitioning by dynamic priorities: Fair and efficient resource-sharing by several services

  • Debasis Mitra
  • Ilze Ziedins
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1044)

Abstract

We propose a scheme for sharing an unbuffered resource, such as bandwidth or capacity, by various services. The scheme assigns a nominal capacity to each service class and implements a form of virtual partitioning by means of state-dependent priorities. That is, instead of each class of traffic having a fixed priority, as in traditional trunk reservation schemes, the priorities depend on the state of the system. An approximate method of analysis based on fixed point equations is given. Numerical results are obtained from the approximation, exact computations and simulations. The results show that the scheme is robust, fair and efficient.

Keywords

Arrival Rate Optimal Policy Blocking Probability Spare Capacity Nominal Capacity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Ash, G.R., Chen, J.S., Frey, A.E., Huang, B.D.: Real-time network routing in an integrated network. Proceedings of the International Teletraffic Congress (ITC-13), Copenhagen (1991).Google Scholar
  2. Foschini, G.J., Gopinath, B., Hayes, J.F.: Optimum allocation of servers to two types of competing customers. IEEE Trans. Comm. COM-29 (1981) 1051–1055.CrossRefGoogle Scholar
  3. Gopal, I.S., Stern, T.E.: Optimal call blocking policies in an integrated services environment. Proceedings of the Conference on Information Sciences and Systems, Johns Hopkins University (1983) 383–388.Google Scholar
  4. Kelly, F.P.: Loss networks. Ann. Appl. Prob. 1 (1991) 319–378.Google Scholar
  5. Kraimeche, B., Schwartz, M.: Traffic access control strategies in integrated digital networks. Proceedings of Infocom '84 (1984) 230–235.Google Scholar
  6. Mason, L., Dziong, Z., Tetreault, N.: Fair-efficient call admission control policies for broadband networks. Proceedings of Globecom '92 (1992).Google Scholar
  7. Ross, K.W.: Multirate Loss Models for Broadband Telecommunications Networks. Springer (1995).Google Scholar
  8. Ross, S.M.: Introduction to Stochastic Dynamic Programming. Academic Press (1983).Google Scholar
  9. Tijms, H.C.: Stochastic Modelling and Analysis: A Computational Approach. Wiley (1986).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Debasis Mitra
    • 1
  • Ilze Ziedins
    • 2
  1. 1.AT&T Bell LaboratoriesMurray HillUSA
  2. 2.Dept. of StatisticsUniversity of AucklandAucklandNew Zealand

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