Design of a fair bandwidth allocation policy for VER traffic in ATM networks

Citation
Sk. Biswas et R. Izmailov, Design of a fair bandwidth allocation policy for VER traffic in ATM networks, IEEE ACM TN, 8(2), 2000, pp. 212-223
Citations number
12
Categorie Soggetti
Information Tecnology & Communication Systems
Journal title
IEEE-ACM TRANSACTIONS ON NETWORKING
ISSN journal
10636692 → ACNP
Volume
8
Issue
2
Year of publication
2000
Pages
212 - 223
Database
ISI
SICI code
1063-6692(200004)8:2<212:DOAFBA>2.0.ZU;2-I
Abstract
Since real-time variable bit rate (VBR) traffic is inherently bursty, dynam ic bandwidth allocation is necessary for ATM streams that carry VER traffic . In order to provide quality-of-services (QoS) guarantees and to reduce th e computational complexity, an hybrid of guaranteed and dynamic adaptive al location scheme requires to be implemented. Typical dynamic allocations to competing streams are done in the form of linear proportions to the bandwid th requirements, We show that during temporary link congestion such proport ional arrangements can give rise to unequal queue growth and, subsequently, degraded QoS, This is found to be true even for streams that belong to the same VER class and share identical long term traffic characteristics and Q oS requirements. In this paper, four allocation algorithms are presented an d analyzed in terms of their fairness and QoS potential for real-time VER t raffic, We propose and show that a novel allocation strategy, termed as Min max, solves the mentioned problem of unfairness within a class. By maintain ing a fair distribution of buffer length across the streams of a class, the proposed policy can achieve better and fairer QoS performance compared to the traditional methods. We present analytical results, proofs and a simula tion study of the described algorithms, Four allocation policies for handli ng MPEG VER video streams are simulated in the context of a wireless ATM (W ATM) medium access control. The results show that in certain scenarios, the Minmax strategy can reduce losses by an order of magnitude, while decreasi ng delays substantially.