CSE 422 Modelling and Simulation

Probability, random variables and their properties, mathematical expectation, specific discrete and continuous random variates (Poisson, exponential, etc.). Simulation tools, random number and variate generation, event serialisation and time advance algorithms; process and resource classes, Performance measures, model instrumentation and result presentation. Simple stochastic processes – discrete time Markov chains, continuous time Markov processes; Poisson process, Birth and Death process and their application to the simple (e.g. M/M/1) queues. More advanced queuing theory – multi-server queues, non-Markovian queues, networks of queues. mean value analysis (analytic derivation of throughput, utilisation, mean queue size and delay). Applications – case studies in computer systems and networks using analysis and simulation, advanced simulation software.