Timothy D. Neame

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This paper presents the Poisson Pareto burst process (PPBP) as a simple but accurate model for Internet traffic. It presents formulae relating the parameters of the PPBP to measurable traffic statistics, and describes a technique for fitting the PPBP to a given traffic stream. The PPBP is shown to accurately predict the queueing performance of a sample(More)
A much clearer picture of the progress towards an integrated high speed multi-service network is now emerging. Such networks were anticipated over twenty years ago, at a time when packet switching was just another way to transmit data. Now the technology is so mature that media barons are organising their investments in order to take advantage of the proot.(More)
This paper provides means for performance evaluation of a queue with Poisson Pareto Burst Process (PPBP) input. Because of the long range dependent nature of the PPBP, straightforward simulations are unreliable. New analytical and simulation techniques are described in this paper. Numerical comparison between the results shows consistency. Conservative(More)
This paper presents steps towards creating a general model for aggregated traffic streams. We show that fitting the mean, variance and Hurst parameter is insufficient to consistently model a long range dependent traffic stream. A fourth parameter, the “level of aggregation,” is required. We also show that with increased aggregation, the behaviour of a(More)
In this paper we examine the usefulness of the M/Pareto process as a model for broadband traffic. We show that the queueing performance of the M/Pareto process depends upon the level of aggregation in the process. When the level of aggregation is high, the M/Pareto converges to a long range dependent Gaussian process. For lower levels of aggregation, the(More)
There have been many queuing analyses for a single server queue fed by an M/G/∞ traffic process, in which G is a Pareto Distribution, that focus on certain limiting conditions. In this paper we enhance the so-called Quasi-Stationary (QS) approximation – a queuing analysis introduced previously that provides an algorithm for computation of an accurate(More)