A capacity allocation rule for ATM networks

One of the key issues is how an ATM network estimates the amount of capacity required for supporting a particular application. In this paper, we consider an ATM network as a flexible multi-rate "circuit switched" network with ATM transport, and identify each application (i.e., traffic source) by a metric, namely its equivalent capacity. The objective of this paper is to determine a rule for estimating the equivalent capacity of the application from its traffic descriptor. We model the cell stream of an application its a point process source, and use the Shannon noiseless coding theorem and entropy rate of point processes to derive its equivalent capacity. The resulting rule shows that the equivalent capacity of an application only depends on its peak rate and mean rate. Furthermore, the rule indicates that (i) the equivalent capacity of an application is linearly dependent on the logarithm of its burstiness, and (ii) it is more efficient to multiplex different streams of a multimedia application at higher layers. We also analyze the performance of a network node that operates according to the capacity allocation rule and supports a number of identical bursty applications to obtain its cell loss ratio. The numerical results with bursty data applications indicate that the node satisfies the QOS requirements of stringent bursty applications, and the rule provides a relatively conservative estimate of the required capacity of an application.<<ETX>>

[1]  Luigi Fratta,et al.  Bandwidth assignment in prioritized ATM networks , 1990, [Proceedings] GLOBECOM '90: IEEE Global Telecommunications Conference and Exhibition.

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

[3]  F. Papangelou,et al.  On the entropy rate of stationary point processes and its discrete approximation , 1978 .

[4]  Aurel A. Lazar,et al.  Joint Scheduling and Admission Control for ATS-Based Switching Nodes , 1992, SIGCOMM.

[5]  G. Niestegge,et al.  The leaky bucket policing method in the ATM network , 1990 .

[6]  Gerd Niestegge,et al.  The ‘leaky bucket’ policing method in the ATM (asynchronous transfer mode) network , 1990 .

[7]  Janusz Filipiak Structured systems analysis methodology for design of an ATM network architecture , 1989, IEEE J. Sel. Areas Commun..

[8]  Andrew J. Viterbi,et al.  Principles of Digital Communication and Coding , 1979 .

[9]  F. Vakil Can Shannon Coding Theorem Play A Role In ATM Traffic Management? , 1993, LEOS 1993 Summer Topical Meeting Digest on Optical Microwave Interactions/Visible Semiconductor Lasers/Impact of Fiber Nonlinearities on Lightwave Systems/Hybrid Optoelectronic Integration and Packagi.

[10]  G. Gallassi,et al.  Resource management and dimensioning in ATM networks , 1990, IEEE Network.

[11]  Eugen Wallmeier A connection acceptance algorithm for ATM networks based on mean and peak bit rates , 1990 .

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

[13]  P. Brémaud Point Processes and Queues , 1981 .

[14]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[15]  M. Decina,et al.  Bandwidth assignment and virtual call blocking in ATM networks , 1990, Proceedings. IEEE INFOCOM '90: Ninth Annual Joint Conference of the IEEE Computer and Communications Societies@m_The Multiple Facets of Integration.

[16]  Charles F. Hockett,et al.  A mathematical theory of communication , 1948, MOCO.

[17]  Donald L. Snyder,et al.  Random point processes , 1975 .

[18]  Kohei Shiomoto,et al.  Dynamic Call Admission Control in ATM Networks , 1991, IEEE J. Sel. Areas Commun..

[19]  H. Saito New dimensioning concept for ATM networks , 1990 .

[20]  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.

[21]  H. Saito,et al.  On congestion control in ATM networks , 1991, IEEE LTS.

[22]  P. Brémaud Point processes and queues, martingale dynamics , 1983 .

[23]  James Roberts,et al.  Traffic Control in the B-ISDN , 1993, Comput. Networks ISDN Syst..