Cloud and Edge Computing

Course goals

• understands the key concepts and underlying principles of cloud and edge computing architectures, and Is able to explain virtualization techniques, its abstractions and enabling technologies.
• can explain and characterize the advantages and disadvantages of cloud-edge abstraction models, such as infrastructure-as-a-Service (IaaS), platform-as-a-service (PaaS), software-as-a-service (SaaS).
• is able to apply and compare different cloud and edge computing programming models and application execution models, understand their trade-offs and benefits in the context of IoT applications.
• can analyze the performance, scalability, and consistency characteristics of cloud and edge systems and make informed decisions about resource and data storage management strategies, including load balancing, auto-scaling, and fault tolerance.
• is able to develop, and analyze real-world cloud and edge applications, and apply the best practices and common pitfalls associated with designing, developing, and deploying these systems.
• can document and communicate effectively about cloud and edge computing concepts and technologies in both written and oral formats, and work collaboratively with teams to develop cloud and edge applications.

Assessment
The course will be assessed as follows:

• group assignment (50% of the final mark)
• individual research paper writing (40%)
• individual poster presentation (10%)
• Individual lab assignments (mandatory pass-no pass exercise)
• individual peer review (mandatory pass-no pass exercise)

To qualify for a repair of the final result the mark needs to be at least a 4, or “AANV”.

Prerequisites
Students must be comfortable and have good experience with one of the programming languages (e.g., Python, Java, Go, etcetera). Students should have a basic knowledge of Linux command-line operations, including basic shell scripting and familiarity with common Linux commands.
Familiarity with data structures and algorithms, computer networks are highly recommended.

Content

This course aims to provide an in-depth exploration of cloud and edge computing concepts.
The course will cover fundamental cloud and edge computing topics such as virtualization and its enabling technologies, application programming paradigms and execution models, resource management, large-scale data storage, performance management and will also briefly discuss  IoT integration with cloud and edge.
Through a combination of lectures, readings, workshops, and hands-on projects, students will gain theoretical and practical experience in designing, modeling, analyzing, developing, and deploying cloud and edge applications that can scale to meet the needs of modern distributed computing environments.

Course form
Lectures, guest lectures, workshops.
Lectures: 2 meetings per week,. Attendance requirement: yes
Workshop/seminar: 1 meeting per week. Attendance requirement: yes

Literature

• Compulsory: Marinescu, D.C. "Cloud Computing, Theory and Practice", 3rd edition, 2022
• Recommended:  Kai Hwang, Jack Dongarra and Geoffrey Fox "Distributed and Cloud Computing: From Parallel Processing to the Internet of Things", 1st edition, 2011
• Other forms of reading: mandatory and recommended list of research papers (to be announced one week before the lecture starts)