Effective bandwidths for multiclass Markov fluids and other ATM sources

The authors show the existence of effective bandwidths for multiclass Markov fluids and other types of sources that are used to model ATM traffic. More precisely, it is shown that when such sources share a buffer with deterministic service rate, a constraint on the tail of the buffer occupancy distribution is a linear constraint on the number of sources. That is, for a small loss probability one can assume that each source transmits at a fixed rate called its effective bandwidth. When traffic parameters are known, effective bandwidths can be calculated and may be used to obtain a circuit-switched style call acceptance and routing algorithm for ATM networks. The important feature of the effective bandwidth of a source is that it is a characteristic of that source and the acceptable loss probability only. Thus, the effective bandwidth of a source does not depend on the number of sources sharing the buffer or the model parameters of other types of sources sharing the buffer. >

[1]  J. Gärtner.  On Large Deviations from the Invariant Measure , 1977 .

[2]  D. Mitra,et al.  Stochastic theory of a data-handling system with multiple sources , 1982, The Bell System Technical Journal.

[3]  R. Ellis,et al.  LARGE DEVIATIONS FOR A GENERAL-CLASS OF RANDOM VECTORS , 1984 .

[4]  P. Ney,et al.  Large deviations of uniformly recurrent Markov additive processes , 1985 .

[5]  Luigi Fratta,et al.  ATM: bandwidth assignment and bandwidth enforcement policies , 1989, IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond.

[6]  Jonathan M. Pitts,et al.  Analysis of ATM switch model (GEO/ATD/1) with time priorities , 1990 .

[7]  James A. Bucklew,et al.  Large Deviation Techniques in Decision, Simulation, and Estimation , 1990 .

[8]  J. Walrand,et al.  Note on Effective Bandwidth of ATM Traffic , 1991 .

[9]  Hamid Ahmadi,et al.  Equivalent Capacity and Its Application to Bandwidth Allocation in High-Speed Networks , 1991, IEEE J. Sel. Areas Commun..

[10]  Thomas E. Stern,et al.  Analysis of separable Markov-modulated rate models for information-handling systems , 1991, Advances in Applied Probability.

[11]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .

[12]  Jean C. Walrand,et al.  Review of 'Large Deviation Techniques in Decision, Simulation, and Estimation' (Bucklew, J.A.; 1990) , 1991, IEEE Trans. Inf. Theory.

[13]  Frank P. Kelly,et al.  Effective bandwidths at multi-class queues , 1991, Queueing Syst. Theory Appl..

[14]  Richard J. Gibbens,et al.  Effective bandwidths for the multi-type UAS channel , 1991, Queueing Syst. Theory Appl..

[15]  Anwar Elwalid,et al.  Fluid models for the analysis and design of statistical multiplexing with loss priorities on multiple classes of bursty traffic , 1992, [Proceedings] IEEE INFOCOM '92: The Conference on Computer Communications.

[16]  Roch Guérin,et al.  A unified approach to bandwidth allocation and access control in fast packet-switched networks , 1992, [Proceedings] IEEE INFOCOM '92: The Conference on Computer Communications.

[17]  G. Parmigiani.  Large Deviation Techniques in Decision, Simulation and Estimation , 1992 .

[18]  Cheng-Shang Chang.  Stability, Queue Length and Delay, Part 11: Stochastic Queueing Networks , 1992 .

[19]  Debasis Mitra,et al.  Effective bandwidth of general Markovian traffic sources and admission control of high speed networks , 1993, TNET.