After completing this course successfully, the student can:|
• translate simple system-related performance problems into adequate performance models and (in some cases) solve these model with analytical means;
• set-up and solve simple discrete- and continuous-time Markovian models;
• analytically solve simple performance models of M/M/1 and M/G/1 type;
• analytically solve simple open and closed queuing networks (Jackson queuing networks and Gordon-Newell queuing networks, respectively);
• set up a simple event-based discrete-event simulation;
• explain the role and impact model-based performance evaluation in comparison to measurements and simulations to investigate performance problems.
The objective of this course is to gain insight, through the use of simple models, into the performance and dimensioning of computer-communication systems. To that aim, simple queuing models are studied and used for the analysis and evaluation of systems, such as switches, access mechanisms in local area networks and broadband networks. Different modelling approaches are considered, such as Markov chains, queuing networks and simulation. These models are used to understand the behavior of the systems being investigated.|
Students are expected to have a Bachelor's degree and need to have:
• working knowledge in probability theory and statistics, as typically taught in introduction courses on probability theory, so that they can compute expected values, variances, etc.
• a basic understanding of layered communication protocols/systems, as taught in a course like Telematicasystemen en Toepassingen (192610000), or the module Network Systems