Objectives
This course aims to familiarise the students with the diverse aspects of scheduling theory and its application: from a single machine system to large-scale distributed systems and communication.
Learning outcomes
Knowledge:
Upon completion of this course, the student:
- Has the fundamental knowledge of scheduling theory, traditional algorithms, modelling different scheduling problems, particularly for single machine system, parallel system, large-scale cluster computing environment.
- Has the knowledge on scheduling mechanisms in key enabler technologies of cluster computing, e.g. container technology and kubernetes.
- Are familiar with scheduling mechanisms in communication within a single machine system, in 4G/5G, in message broker systems and in message queue systems.
Skills:
Upon completion of this course, the student:
- Can investigate a scheduling problem and address it with a proper algorithm, be it with a heuristic, metaheuristic, or dynamic programming one.
- Can investigate and address the scheduling problem of a scalable infrastructure in their work environment, particularly with container technology and Kubernetes.
- Will have the knowledge of scheduling network resources and communication channels with some of the key technologies such as Kafka and RabbitMQ.
Preferred Soft Prerequisite
Good knowledge of Scheduling concepts at the bachelor level is a must. This course needs a good knowledge on Python or any other programming language and familiarity with Linux environment. Students should be able to debug basic errors, ssh other machines, and basic knowledge on cloud computing & container virtualization is a plus.
- You will have an extra advantage if you have successfully completed the DevOps course or cloud computing course or any other similar course.
Lecturers
- Chinmaya Kumar Dehury
Learning environment
- Face-to-face learning
- On Special Request from the student, online delivery of lecture can be arranged
- Final Exam may happen in online/offline mode, stay tuned for the updates.
| Languages of instruction | : | English |
| Levels of study | : | Master's studies |
| Max no. of students | : | 20 |
Schedule & Location
| Lectures | : | Monday | : | 16:15-18:00 : Room no. 2010 |
| Practice | : | Tuesday | : | 14:15-16:00 : Room no. 1017 |
Contact chinmaya.dehury(at)ut.ee if needed.