Department of Computing
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> # Performance Analysis

> Lecturer s : Peter Harrison (homepage) , Giuliano Casale (homepage)
> For course notes click on the lecturers homepages.

> To introduce analytical modelling techniques for predicting computer system performance.
> Motivation and survey; the need for performance prediction in optimisation and system design.
> Basic probability theory: renewal processes; Markov processes; birth and death processes; the single server queue; Little's law; embedded Markov chain; M/G/1 queue; queues with priorities; queueing networks - open, closed, multi-class; equilibrium state space probabilities, proof for single class; normalising constants; computation of performance measures; convolution algorithm; mean value analysis; application to multi-access systems with thrashing.
> Decomposition and aggregation: Norton's theorem; M/M/n queue; multiple independent parallel servers.
> The course also offers an introduction to performance modelling using a stochastic process algebra, eg PEPA. To include: expansion law, apparent rate, steady-state
> analysis, transient state analysis through uniformisation and reward
> vectors.

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