QoS adaptation and flow filtering in ATM networks

Yeadon, Nicholas; Garcia, Fabien; Campbell, Andrew T.; Hutchison, David

doi:10.1007/3-540-58494-3_17

Cited by 23 publications

(16 citation statements)

References 7 publications

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“…Here individual receivers may have differing QoS capabilities to consume audio-visual flows; QoS filtering helps to bridge this heterogeneity gap, while simultaneously meeting individual receivers' QoS requirements [90].…”

Section: Qos Management Mechanismsmentioning

confidence: 99%

A survey of QoS architectures

1998

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Over the past several years there has been a considerable amount of research within the field of quality-ofservice (QoS) support for distributed multimedia systems. To date, most of the work has been within the context of individual architectural layers such as the distributed system platform, operating system, transport subsystem and network layers. Much less progress has been made in addressing the issue of overall end-to-end support for multimedia communications. In recognition of this, a number of research teams have proposed the development of QoS architectures which incorporate QoS-configurable interfaces and QoS driven control and management mechanisms across all architectural layers. This paper examines the state-of-theart in the development of QoS architectures. The approach taken is to present QoS terminology and a generalized QoS framework for understanding and discussing QoS in the context of distributed multimedia systems. Following this, we evaluate a number of QoS architectures that have emerged in the literature.

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Section: Qos Management Mechanismsmentioning

confidence: 99%

A survey of QoS architectures

1998

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“…Assume task T defines a pair of parameter tuning actions: a function F that can increase CPU utilization in T2 ,and a function Fd that can decrease CPU utilization in T2. We also define control error values e(k) as follows: e(k) = r(k) -u(k) (8) Obviously, the universe ofdiscourse U in the fuzzy set theory15 corresponds to the set of all possible values of e(k). We can thus define the membership function PositiveError of a fuzzy set PositiveSet as a function of:…”

Section: Translation For Parameter Liming Actionsmentioning

confidence: 99%

<title>End-to-end QoS support for adaptive applications over the Internet</title>

Nahrstedt³

et al. 1998

SPIE Proceedings

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In current end systems, multiple flexible, complex and distributed applications concurrently share and compete both end systems resources and transmission bandwidth of heterogeneous multi-protocol networks, especially the Internet. Our objective is to enable adaptation awareness in these applications to fully cope with the dynamics in resource availability over the heterogeneous Internet, as well as fluctuations in Q0S requirements of the applications themselves. In this paper, we present the theoretical and practical aspects of a Task Control Model implemented in the middleware layer, which applies control theoretical approaches to utilize measurement-based samples monitored in the network traffic, as well as resource and Q0S demand dynamics observed in the end systems.In our Task Control Model, we introduce Adaptation Tasks for controlling the adaptive behavior of applications, and Observation Tasks for measurements of traffic and end systems resources. We have made several contributions based on the Task Control Model. First, we are able to quantitatively analyze the stability and responsiveness properties of adaptive algorithms, as well as maintaining fairness properties among all applications. Secondly, we present specific translation mechanisms to theoretical output of Adaptation Tasks to semantic adaptive behavior within the applications. Thirdly, we explore necessary enabling service platforms in the middleware level to embrace the Task Control Model. Finally, the theoretical analysis in the paper is carried out in the context of a distributed visual tracking application, in order to demonstrate the effects of adaptation in real systems.

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“…The main action of interest here is that of atklpt. For example filters can be instantiated which will reduce the playout quality to another level, possibly alleviating the congestion problem while providing a playout quality which is still acceptable to the user (Yeadon, 1994).…”

Section: Flow Managementmentioning

confidence: 99%

QoS support for distributed multimedia communications

Garcia

Hutchison

Mauthe

et al. 1996

Distributed Platforms

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The nature of distributed multimedia applications is such that they require multipeer communication support mechanisms. Multimedia traffic needs to be delivered to end-systems, networks and end-users in a form that they can handle while satisfying the constraints imposed by the multimedia application. Quality of Service (QoS) mechanisms are required that can ensure full quality media play out at high-performance workstations while at the same time providing appropriately filtered lower quality media for playout at low-end systems. Existing multicast support mechanisms are deficient for this purpose, in a heterogeneous environment, because they work on a lowest common denominator premise where the quality provided depends on the least capable link or node involved in the multicast session . In this paper we discuss a QoS model to provide receiver-dependent QoS based on filtering techniques, and we present initial experimental results.

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QoS adaptation and flow filtering in ATM networks

Cited by 23 publications

References 7 publications

A survey of QoS architectures

A survey of QoS architectures

<title>End-to-end QoS support for adaptive applications over the Internet</title>

QoS support for distributed multimedia communications

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