Fergal Toomey

Entropy of ATM traffic streams: a tool for estimating QoS parameters

For the purposes of estimating quality-of-service parameters, it is enough to know the large deviation rate-function of an ATM traffic stream; modeling procedures can be bypassed if we can estimate the rate-function directly, exploiting the analogy between the rate-function and thermodynamic entropy. We show that this proposal is soundly based on statistical sampling theory. Experiments on the Fairisle ATM network at the University of Cambridge have established that it is feasible to collect the required data in real time. >

Statistical properties of a near-optimal measurement-based CAC algorithm

Our algorithm, called Mosquito, allows sources to be ignorant of their statistics but offers near-optimal utilisation of the network. Our approach is based on large deviation theory: the large deviation rate-function (entropy) of bursty ATM traffic can be estimated from measurements of traffic activity. The entropy can be used to determine the bandwidth requirement of the traffic. In this paper, we explain the basic ideas behind the algorithm and describe its implementation. We present some results of a statistical investigation of the performance of the Mosquito CAC algorithm comparing it with that of various modifications of the algorithm.

Invited Practical connection admission control for ATM networks based on on-line measurements

We present algorithms for connections admission control (CAC) in an ATM network based upon the use of on-line measurement and estimation. (The algorithms described in this paper are the subject of a UK patent application.) Our approach uses the theory of large deviations, which is a valuable tool for reasoning about rare events in stochastic systems. We have shown previously that the large deviations rate function, or entropy, of ATM traffic can be estimated from activity measurements. This can be used to determine the effective bandwidth of the traffic. In this paper we present practical measurement-based CAC algorithms which are computationally efficient, and can be used with traffic whose statistical characteristics are unknown.

Measurement-based resource allocation for multimedia applications

Modern networks are now capable of guaranteeing a consistent quality of service (QoS) to multimedia traffic streams. A number of major operating system vendors are also working hard to extend these guarantees into the end-system. In both cases, however, there remains the problem of determining a service rate sufficient to ensure the desired quality of service. Source modeling is not a sustainable approach in the network case and it is even less feasible to model the demands of multimedia applications. The ESPRIT measure project is successfully using on-line measurement and estimation to perform resource allocation for bursty traffic in ATM networks. In this paper we consider the applicability of the same theory to resource allocation in a multimedia operating system which offers QoS guarantees to its applications.

Estimating QoS parameters for ATM traffic using its entropy

How will ATM carriers allocate the band-width required to guarantee the quality-ofservice promised in their customer contracts? How can customers exploit to their advantage the tariff structures offered by the carriers? Both carrier and customer will need to measure QoS (quality-of-service) parameters.

Distribution-free confidence intervals for measurement of effective bandwidths

Hoeffdings inequality can be used in conjunction with the declared parameters of a traffic source, such as its peak rate, to obtain confidence intervals for measurements of the traffics effective bandwidth. We describe a variety of interval-estimation procedures based on this idea, designed to provide differing degrees of robustness against non-stationarity. We also discuss how to compute confidence intervals for the effective bandwidth of an aggregate of traffic sources.

Exploring the queueing behaviour of ATM switches

Abstract In this paper we describe methods which we have used to verify queueing models of two ATM switches, namely the Fairisle ATM switch developed at Cambridge University Computer Laboratory and an AT&T Globeview 2000 switch installed in the experimental test-bed at Telia Research Laboratories. Our approach relies on methods from large deviation theory, which we believe provides an appropriate scale on which agreement may be expected between a simple model and an actual ATM switch. We found that for the purpose of estimating delays the single-server queue provides an adequate model, at the large deviation scale, of both switches under the conditions investigated. However it does not reproduce the output behaviour of the Globeview switch at high loads. The model was evaluated using both analytic techniques and simulation. We emphasize that the model is not exact, indicating that very complex models may be required in order to obtain results more detailed than those afforded by large deviation theory. This calls into question the common practice of using detailed models of network traffic in conjunction with simplified models of the network itself.