Performance Modelling

This course runs in Semester 1 on Tuesdays and Fridays at 12:10.

About the course:

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.

Lecture notes:

The course lecture notes are by Jane Hillston.
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
More Complex Markov Processes Lecture 4
Queueing Networks Lecture 5
Solving Queueing Models Lecture 6
Stochastic Petri Nets Lecture 7
More about GSPN Models Lecture 8
Using a GSPN for Performance Evaluation Lecture 9
PEPA Lecture 10
PEPA Case Study: Web Service Composition Lecture 11
Simulation Models: Introduction and Motivation Lecture 12
The PEPA Plug-in for Eclipse
Random Variables and Simulation Lecture 14
Tackling state space explosion in PEPA models Lecture 15
Model Validation and Verification Lecture 16
Validation exercise
Parameterisation and Workload Characterisation Lecture 17
Comparison of Techniques

Software and models:

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.

Maple

The SPNP tool is available as a tarball here.
You should copy it into your DICE account. Within the directory you will find a README file with instructions for running SPNP on a CSPL file on a DICE machine. Some example CSPL files are available below; another is available within the directory you download. Before you complete the second practical you must print and sign the SPNP student license agreement document

SPNP

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.

PEPA

This note gives some information about undertaking scalable analysis with the PEPA tools. It can be seen as a supplement to Lecture Note 15, and may be useful for MSc students undertaking Practical 2.

Coursework and Feedback:

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.
Individual feedback and a specimen solution will be provided.

Formative feedback will be provided throughout the course in a variety of forms:

Books:

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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