Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
After the course, the student
Is able to apply Markov processes and regenerative processes to model various computer and communication systems;
Is able to construct, analyse and optimise stochastic queueing models to evaluate the performance of the system;
Comprehends selected applications of the performance analysis of modern computer and communication systems.
Schedule: 20.04.2021 - 02.06.2021
Teacher in charge (valid 01.08.2020-31.07.2022): Samuli Aalto, Pasi Lassila
Teacher in charge (applies in this implementation): Samuli Aalto, Pasi Lassila
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
1) ELEC-C7210 recap.
2) Stochastics: Conditional expectation. Phase-type distributions. Reversibility. Regenerative processes.
3) Single-server queues: M/G/1-FIFO queue. M/G/1-PS queue. Optimal scheduling problem. Applications.
4) Multi-server queueing systems: Separability. Optimal dispatching problem. Applications.
5) Queueing networks: Open queueing networks. Closed queueing networks. Applications.
6) Resource sharing: Max-min fairness, Alpha-fairness, Balanced fairness. Applications.
Assessment Methods and Criteria
Compulsory: Examination (100%), exercises
Contact hours 49 hours
Independent learning: 82 hours
Substitutes for Courses
SDG: Sustainable Development Goals
8 Decent Work and Economic Growth