Microsoft Word – CSC8106 coursework full 2018-corrected.docx
CSC8106 System Evaluation
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Coursework 2022
• Summative assignment due 16.00 on 18th November 2022.
• This exercise is worth 100% of the module mark.
• You should attempt aspects of this exercise.
• Answers should be included in a single MS Word or PDF file submitted into NESS.
– you should include PEPA input files, screen shots, graphs and diagrams as appropriate,
along with clear explanations of what you have done.
Any questions just email me at
To tackle this exercise you will need to use PEPA (Performance Evaluation Process Algebra)
http://www.dcs.ed.ac.uk/pepa/ and the PEPA Eclipse Plug-in, which is available from
http://www.dcs.ed.ac.uk/pepa/tools/. You will need to have Eclipse installed (which also requires
you to have Java installed first). Install the tools before attempting the exercises. Note that the PEPA
Eclipse Plug-in is not compatible with the latest version of Eclipse which installed in the lab. As such,
you will need to install an older version of Eclipse first (version 2020-09 (4.17.0)).
For this exercise you will need to analyse a model using the PEPA Eclipse Plug-in. You could define
your own model, but a more reliable approach would be to take one from the literature. There is a
substantial archive of papers on PEPA at http://www.dcs.ed.ac.uk/pepa/papers/ and there are more
in Google Scholar. Some suggestions – all available in Canvas – for papers describing possible systems
to study include:
• D.R.W. Holton and J.P.N. Glover. An SPA performance model of a production cell. In D.
Kouvatsos, editor, Proceedings of the Thirteenth UK Performance Engineering Workshop,
pages 6/1-6/6, Bradford, 1997.
• H. Bowman, J. Bryans, and J. Derrick. Analysis of a multimedia stream using stochastic
process algebra. In C. Priami, editor, Sixth International Workshop on Process Algebras and
Performance Modelling, pages 51-69, Nice, September 1998.
• Y Zhao and N Thomas. Efficient solutions of a PEPA model of a key distribution centre.
Performance Evaluation 67 (8), 740-756, 2010.
• SNS Kamil, N Thomas, A case study in inspecting the cost of security in cloud computing,
Electronic Notes in Theoretical Computer Science, 318, 179-196, 2015.
• C Abdullah, N Thomas, A PEPA model of IEEE 802.11b/g with hidden nodes, Computer
Performance Engineering, LNCS 9951, 126-140, 2016.
• X Chen, J Ding, N Thomas, Dynamic Scheduling Policy for Patient Flow in a Smart
Environment, Chinese Journal of Electronics 26 (3), 530-536, 2017.
• A Alssaiari, RA JM Gining, N Thomas, Modelling Energy Efficient Server management
policies in PEPA. 3rd International Workshop on Energy-aware Simulation (ENERGYSIM’17),
• M Alotaibi, N Thomas, Performance Evaluation of a Secure and Scalable E-Voting
Scheme Using PEPA. In: Balsamo S., ., Vicario E. (eds) in Quantitative
Methods in Informatics. InfQ 2017. Communications in Computer and Information Science,
vol 825. Springer, 2018.
• A Alkoradees, N Thomas, Optimising Health Systems, 34th Annual UK Performance
Engineering Workshop, 2018.
• O Almutairi and N Thomas. Performance Modelling of an Anonymous and Failure Resilient
Fair-Exchange E-Commerce Protocol. In Proceedings of the 2019 ACM/SPEC International
Conference on Performance Engineering (ICPE ’19), 5-12, 2019.
• O Almutairi, N Thomas, Performance modelling of attack graphs, Eleventh International
Workshop on Practical Applications of Stochastic Modelling, 2022.
• , , , Aad van Moorsel and
Verifier’s Dilemma in : A Quantitative Analysis, International
Conference on Quantitative Evaluation of Systems, 2022.
Copies of all these papers are available in the module pages in Canvas.
For the exercise you will produce a report which covers the following:
a) A clear and detailed description of the system you are going to model.
b) Implementation your model in the PEPA Eclipse Plug-in, with screenshots.
c) Identification of suitable metrics and parameter values, justifying your choices. Remember
to include all your parameters.
d) Use of the tool to derive results based on these values and measures.
e) Presentation of graphs of the results, highlighting any interesting or noteworthy features.
f) Discussion of how your model and/or analysis could be extended to consider different
features of the system. For example, you could present analysis based on different
parameters (with justification), different metrics, different solution methods, an alteration to
the model specification, or some combination of these.
A minimum deliverable would be to reproduce some results from the original paper with your own
descriptions and graphs derived from the tool. A more advanced deliverable would also extend
the model or analysis giving detailed descriptions of the new results that you have found.
Remember to include references to all source material used and while model specifications can
be reproduced with citation, any written descriptions should be in your words to convey your
understanding. All submissions will be checked for plagiarism.
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