This course runs in Semester 1 on Mondays and Thursdays at 10:00.
The first lecture/session will be on Monday 25th September.
The sessions will take place in room G15, 7 Bristo Square.
NOTE: there will be no sessions during Week 1.
This course teaches various aspects of computer-aided modelling for performance evaluation of (stochastic) dynamic systems. The emphasis is on stochastic modelling of computer systems and communication networks; however other dynamic systems such as manufacturing systems will also be considered. The central concept of the course will be that a model, as well as being an abstract representation of a system, is a tool which we can exploit to derive information about the system. The more detail we invest in the model, the more sophisticated the information we can extract from it. As the course progresses the models will become increasingly detailed; the corresponding solution techniques will similarly become more complex, relying on increasing levels of computer assistance and visualisation.
You can find some useful mathematical background material for the course here.
If you are not already comfortable with all these concepts you will need to put in some additional work to begin with to get up to speed. This material will be assumed.
There is a complete set of course lecture notes to accompany the course prepared by
Lecture notes, slides and recorded lectures will be available in LEARN at least one week before the corresponding session.
Sessions and Topics Modelling and Simulation Operational Laws Constructing and Solving Markov Processes More Complex Markov Processes Queueing Networks Solving Queueing Models Stochastic Petri Nets More about GSPN Models Using a GSPN for Performance Evaluation PEPA The PEPA Plug-in for Eclipse PEPA Case Study: Rap Genius on Heroku Simulation Models: Introduction and Motivation Random Variables and Simulation Tackling state space explosion in PEPA models Using the scalable solution techniques with PEPA Model Validation and Verification Parameterisation and Workload Characterisation Comparison of Techniques
The course blog gives a summary of each lecture and session, as well as providing links to any relevant papers or articles which may be of interest.
There will be a final lecture, a revision lecture, in April 2018. This will be announced via the class mailing list.
Over the course we will encounter a number of different approaches to constructing performance models and software tools to support their use. Example models will be made available here and students are encouraged to use the examples, both in the sessions and in private study, to gain a deeper understanding of both the modelling styles and the software tools.
The summative feedback for the course will be two pieces of assessed coursework.
In line with the University's Assessment Regulations there will be a penalty of 5% per day up to 7 calendar days (see for details).
There are no tutorials for this course but individual assistance is available: mail me and make an appointment Jane.Hillston@ed.ac.uk or ad hoc tutorials can be arranged if there is demand.
Individual personalised feedback will be written on your submission and a specimen solution will be provided.
Formative feedback will be provided throughout the course in a variety of forms:
The examples and exercises in class are intended to deepen your understanding of the material of the course and prepare you for the assessed practicals. The revision lecture is an important preparation for the exam.
There is no textbook for this course but extensive notes will be given.
If you want further information on the topics covered you may consider the books in the course booklist.
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