Handbook

This subject will provide the essential theoretical and practical foundations for the design and optimisation of large-scale distributed systems. There is a particular emphasis on the telecommunication network planning as an example, but students will also be exposed to other cases and the knowledge gained will have applications in many diverse domains. The first part will cover the fundamentals of queuing theory. The basic properties of stochastic processes are reviewed. Markov modelling, including discrete Markov processes and its application in describing random sequence of events is presented. Then the properties of exponential distribution, Poisson distribution, M/M/1 queues, queues with finite capacity, queues with general service distribution and open queuing networks are presented. Students will be exposed to properties of these systems by using both analysis and simulation. The second part will cover the basics of graph theory, followed by an introduction to linear optimisation, including Linear Programming, Simplex algorithm, Integer Linear Programming, and the Branch and Bound algorithm. The students will then be exposed to fundamentals of non-linear optimisation and Lagrange Method as well as methods to assess the complexity of a problem. Finally a number of important heuristics for solving large-scale optimisation problems will be presented. Students will experience the various optimisation techniques by using both analysis and simulation.