LEARNING OUTCOMES
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.
Credits: 5
Schedule: 23.04.2024 - 05.06.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Samuli Aalto
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
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) Queueing networks: Open queueing networks. Closed queueing networks. Applications.
5) Resource sharing: Max-min fairness, Alpha-fairness, Balanced fairness. Applications.
6) Multi-server queueing systems: Separability. Optimal dispatching problem. Applications.
Assessment Methods and Criteria
valid for whole curriculum period:
Compulsory: Examination (100%), exercises
Workload
valid for whole curriculum period:
Contact hours 49 hours
Independent learning: 82 hours
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
4 Quality Education
8 Decent Work and Economic Growth
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Spring V
2023-2024 Spring VEnrollment :
Registration for Courses: Sisu