Measurement-Based Admission Control with Aggregate Traffic Envelopes

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Measurement-Based Admission Control with Aggregate Traffic Envelopes (2001)

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by Jingyu Qiu , Edward W. Knightly

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BibTeX

@MISC{Qiu01measurement-basedadmission,
    author = {Jingyu Qiu and Edward W. Knightly},
    title = {Measurement-Based Admission Control with Aggregate Traffic Envelopes},
    year = {2001}
}

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Abstract

The goal of admission control is to support the quality-of-service demands of real-time applications via resource reservation. In this paper, we introduce a new approach to measurement-based admission control for multiclass networks with link sharing. We employ adaptive and measurement-based maximal rate envelopes of the aggregate traffic flow to provide a general and accurate traffic characterization that captures its temporal correlation as well as the available statistical multiplexing gain. In estimating applications' future performance, we introduce the notion of a schedulability confidence level which describes the uncertainty of the measurement-based "prediction" and reflects temporal variations in the measured envelope. We then devise techniques to control loss probability for a buffered multiplexer servicing heterogeneous and bursty traffic flows, even in the regime of a moderate number of traffic flows, which is important in link-sharing environments. Finally, we have developed an implementation of the scheme on a prototype router and performed a testbed measurement study, which together with extensive trace-driven simulations illustrates the effectiveness of the approach in practical scenarios.

Keyphrases

measurement-based admission control aggregate traffic envelope bursty traffic available statistical multiplexing gain moderate number new approach practical scenario extensive trace-driven simulation aggregate traffic flow prototype router link-sharing environment testbed measurement study traffic flow real-time application admission control temporal correlation temporal variation buffered multiplexer resource reservation multiclass network measurement-based prediction loss probability quality-of-service demand measurement-based maximal rate envelope future performance accurate traffic characterization schedulability confidence level

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