This course runs in Semester 2 on Mondays and Thursdays at 10:00. The first lecture was on Monday 16th January.
NOTE: there will be a lecture on Thursday 16th March.
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.
The course lecture notes are by
Lecture notes will be available at least 24 hours prior to each lecture on the webpage and the slides generally within 24 hours after the lecture.
Lectures Slides Modelling and Simulation Lecture 1 Operational Laws Lecture 2 Constructing and Solving Markov Processes Lecture 3 Short online lecture explaining the exercise from Lecture 3 Solution Slides More Complex Markov Processes Lecture 4 Queueing Networks Lecture 5 Solving Queueing Models Lecture 6 Short online lecture explaining the traffic equation exercise Slides Stochastic Petri Nets Lecture 7 More about GSPN Models Lecture 8 Using a GSPN for Performance Evaluation Lecture 9 GSPN exercise sheet Solution slides PEPA Lecture 10 The PEPA Plug-in for Eclipse No corresponding lecture PEPA Case Study: Rap Genius on Heroku Lecture 12 PEPA Exercises Solutions to PEPA Exercises Simulation Models: Introduction and Motivation Lecture 13 Random Variables and Simulation Lecture 14 Tackling state space explosion in PEPA models Lecture 15 Using the scalable solution techniques with PEPA No corresponding lecture Model Validation and Verification Lecture 16 Parameterisation and Workload Characterisation Lecture 17 Comparison of Techniques
There is no lecture to accompany this note:
it is intended to help you revise.
The course blog gives a summary of each lecture and links to any relevant papers or articles which may be of interest.
There will be a final lecture, a revision lecture, in April 2017. 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 to gain a deeper understanding of both the modelling styles and the software tools.
- A ZIP archive of all of the files below
- MatLab script for the multiprocessor with two processors
- MatLab script for the PC LAN with 4 nodes
- the states for the PC LAN with 4 nodes (MatLab input file
- the transitions for the PC LAN with 4 nodes (MatLab input file)
- MatLab calculation for the average number of packets per PC in the 4 node LAN
- MatLab calculation for the average throughput of packets per PC in the 4 node LAN
- MatLab script for the PC LAN with 6 nodes
- the states for the PC LAN with 6 nodes (MatLab input file
- the transitions for the PC LAN with 6 nodes (MatLab input file)
- MatLab calculation for the average number of packets per PC in the 6 node LAN
- MatLab calculation for the average throughput of packets per PC in the 6 node LAN
PIPE (Platform Independent Petri net Editor) is an open source, platform
independent tool used of the creation and analysis of Petri Nets, and some
of their extension, developed at Imperial College. It is implemented in Java
and has a graphical user interface, which makes it very straightforward to use.
The most recent version is PIPEv4.3.0 and it is available for download from
Once you have unpacked the directory/folder PIPEv4.3.0, enter that directory and issue the command ./launch.sh or .\launch.bat according to your operating system, to launch the PIPE tool.
There is a short movie here which may help you with installing the PEPA Plug-in for Eclipse. You will find the plug-in and further instructions at http://www.dcs.ed.ac.uk/pepa/tools/plugin/download.html.
There is an old lecture note about the composition of web services example here, but I will not be lecturing on this example this year.
- ZIP archive of all the files listed below
- PEPA model of the WEB1 example
- PEPA model of the WEB2 example
- PEPA model of the WEB4 example
- PEPA model of Heroku with the random routing policy
- PEPA model of Heroku with the smart routing policy
- PEPA model of the PC LAN example with four nodes
- PEPA model of the PC LAN example with six nodes
- PEPA model of a composition of web services
This note gives some information about undertaking scalable analysis with the PEPA tools. It can be seen as a supplement to Lecture Note 15.
The summative feedback for the course will be two pieces of assessed coursework.
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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