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Dynamic bandwidth allocation for ATM switches

Part of: Limit theorems Stochastic systems and control Markov processes Operations research and management science

Published online by Cambridge University Press:  14 July 2016

Ivy Hsu  and
Jean Walrand
Ivy Hsu*
Affiliation:
University of California, Berkeley
Jean Walrand*
Affiliation:
University of California, Berkeley
*
∗Postal address for both authors: Department of EECS, University of California, Berkeley, CA 94720, USA.
∗Postal address for both authors: Department of EECS, University of California, Berkeley, CA 94720, USA.
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Abstract

We explore a dynamic approach to the problems of call admission and resource allocation for communication networks with connections that are differentiated by their quality of service requirements. In a dynamic approach, the amount of spare resources is estimated on-line based on feedbacks from the network's quality of service monitoring mechanism. The schemes we propose remove the dependence on accurate traffic models and thus simplify the tasks of supplying traffic statistics required of network users. In this paper we present two dynamic algorithms. The objective of these algorithms is to find the minimum bandwidth necessary to satisfy a cell loss probability constraint at an asynchronous transfer mode (ATM) switch. We show that in both schemes the bandwidth chosen by the algorithm approaches the optimal value almost surely. Furthermore, in the second scheme, which determines the point closest to the optimal bandwidth from a finite number of choices, the expected learning time is finite.

Keywords

ADAPTIVE ALGORITHMMARKOV MODULATED FLUID MODELCOUPLINGLAST EXIT TIMELARGE DEVIATIONS

MSC classification

Primary: 93E35: Stochastic learning and adaptive control
Secondary: 60J27: Continuous-time Markov processes on discrete state spaces 90B22: Queues and service 60F05: Central limit and other weak theorems
Type
Research Papers
Information
Journal of Applied Probability , Volume 33 , Issue 3 , September 1996 , pp. 758 - 771
Copyright
Copyright © Applied Probability Trust 1996 

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Footnotes

This research is supported in part by a grant of the Networking and Communications Research Program of the National Science Foundation.

References

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