Unit name | Introduction to Queueing Networks |
---|---|
Unit code | MATH35800 |
Credit points | 10 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 1B (weeks 7 - 12) |
Unit director | Dr. Ayalvadi Ganesh |
Open unit status | Not open |
Pre-requisites |
Math 21400 Probability 2 |
Co-requisites |
None |
School/department | School of Mathematics |
Faculty | Faculty of Science |
Unit aims
To introduce stochastic models for the description and analysis of simple queues and queueing networks.
General Description of the Unit
Queues are a fact of life - in banks, supermarkets, health care, traffic etc. The modelling and evaluation of individual queueing systems (in terms of quantities such as customer arrival patterns, service demands, scheduling priorities for different customer classes, queue size and waiting times) has been a rich source of theory and application in applied probability and operational research. Networks of linked queueing systems have gained wide popularity for modelling and performance-evaluation in telecommunications, computer systems and manufacturing.
The course will introduce relevant concepts in the context of a single server queue before going on to develop models and performance criteria applicable to more general networks. Applications will be explored through homework problems.
Relation to Other Units
The units Information Theory, Financial Mathematics, Queuing Networks and Complex Networks apply probabilistic methods, learnt in Applied Probability 2, to problems arising in various fields.
Additional unit information can be found at http://www.maths.bristol.ac.uk/study/undergrad/current_units/index.html
Students who successfully complete this unit should be able to:
define the concepts of reversed and reversible Markov processes and use them to *construct equilibrium distributions for simple queueing networks; compute the distribution of the queue size as seen in equilibrium by arrivals and departures;
Transferable Skills
The ability to translate practical problems into mathematics and the construction of appropriate probabilistic models.
Lectures and weekly problem sheets, from which work will be set and marked, with outline solutions handed out a fortnight later.
100% Examination
Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.
Reading and references are available at http://www.maths.bristol.ac.uk/study/undergrad/current_units/index.html