Formula for the required capacity of an ATM multiplexer

Document type: Conference Papers
Peer reviewed: Yes
Full text:
Author(s): Markus Fiedler
Title: Formula for the required capacity of an ATM multiplexer
Translated title: Formel för den erforderliga kapaciteten för en ATM multiplexer
Conference name: 14th Nordic Teletraffic Seminar (NTS-14)
Year: 1998
Pagination: 367-379
City: Lyngby, Danmark
Organization: Blekinge Institute of Technology
Department: Dept. of Telecommunications and Mathematics (Institutionen för telekommunikation och matematik)
Dept. of Telecommunications and Mathematics S-37179 Karlskrona
+46 455 38 50 00
Authors e-mail:
Language: English
Abstract: This contribution deals with a formula for the capacity an ATM multiplexer must at least have to accomodate the loss probability demands of all connections. So it can be used for connection admission control as well as for network resource management purposes. The formula is based on the bufferless fluid flow multiplexer model. It allows for a more exact capacity evaluation than if equivalent bandwidths are used on a per-connection basis. On the other hand, it merely requires a computational effort which is comparable to evaluating the mean of a given distribution. Indeed, the bottleneck is the convolution of probability ensity functions, on which the formula operates. Two steps to reduce the computational effort are proposed: a framework for convolution operations, consisting of pre-computed probability density functions, and a suitable truncation of the state space.
Summary in Swedish: Pappret behandlar snabba beräkningar av kapaciteten i datakom nätverk som behövs för att garantera en önskad kvalitetsnivå. Dessa beräkningar grundas på faltningar av bandbredds statistik. Resursbehov, flödesmodell, kapacitetsberäkningar, faltning
Subject: Telecommunications\General
Telecommunications\Fluid Flow Models
Telecommunications\Modelling of Bursty Traffics
Keywords: ATM multiplexing, erformance evaluation, capacity assignment, CAC, NRM, bufferless fluid flow model, convolution algorithm
Note: Unfortunately, the article contained in the proceedings contains errors (an erratasheet was provided). However, the PDF file (see above) is a corrected version.