Edge Computing and Internet of Things, 7.5 credits

Main field of study with advanced study

Courses in computer science, computer engineering or electrical engineering of at least 90 higher education credits, including thesis. Algorithms, Data Structures and Problem Solving 7.5 credits or equivalent. Exemption of the requirement in Swedish is granted. English 6.

The course is included in the Master's Programme in Information Technology 120 credits and as an elective course in the Master's Programme in Embedded and Intelligent Systems 120 credits. The course is also offered as a freestanding course.

The course is intended to develop the student’s knowledge and abilities of how edge computing and Internet of Things (IoT) can be used as a way to meet application demands in intelligent IoT systems. This includes an understanding and use of the IoT architecture with its entities and protocols, from the IoT devices, via middle layers like edge and fog, up to the cloud. It also includes the understanding of the computing and communication technologies used for IoT, as well as the analysis of their constraints, as e.g. performance, power efficiency, memory size, and communication bandwidth. The course also includes the security and privacy issues related to the area of edge computing, IoT, and big data. Further, it is intended to provide the possibility for the student to, from the basis of relevant literature, reflect over and discuss current research and development in regard to highly demanding streaming applications, like advanced sensing or machine learning, at the edge of an IoT system. The student should be able under supervision to implement an edge and IoT systems.

Following successful completion of the course the student should be able to:

Knowledge and understanding

• describe and explain the most important computing and communication technologies, as well as architectures, entities and protocols, used for IoT and edge computing, and discuss their respective advantages, disadvantages, and application opportunities.

Skills and ability

• build a basic IoT system which includes edge computations
• investigate, discuss, and compare architectural design options regarding the trade-off between computations and communication in an IoT system, depending on application demands and resource constraints
• identify, read, and understand relevant scientific publications; review, discuss, and summarize them, and present the findings both orally and in written form

Judgement and approach

• evaluate and reflect on the use of edge computing and IoT methods, protocols, and architectures to create intelligent IoT systems
• evaluate and analyze different types of IoT services and applications with respect to security and privacy issues.

The course is divided into a lecture part, a laboratory part including a small project, and a seminar part.

The lecture part initially gives a motivation for IoT and edge/cloud computing, based on application requirements and resource restrictions. Then it introduces the architectures, entities and protocols used for IoT and edge computing. Example applications and IoT architectures are presented and discussed. This part will also discuss various limitations, such as computing, memory, communication, power, and energy limitations, that will influence future edge and IoT developments. The course will also address relevant security and privacy issues in the area.

The laboratory part provides hands-on experience of edge computing and IoT systems and architectures for the development and use of intelligent IoT systems.

In the seminar part of the course, course participants conduct detailed studies of various subareas and lead seminars in these. The university’s research projects are included in these special studies.

The course is composed of lectures, laboratory sessions, a small project, and student-prepared and student-lead seminars. The lectures will provide the theoretical presentation of edge computing and IoT. In the laboratory sessions the students work in groups and implement parts of an IoT system. The course also includes a mandatory group project work, where students have a chance to solve a realistic and demanding edge computing/IoT problem, using methods and techniques introduced during the course. Finally, each student will prepare and lead a seminar on a current topic in the area of edge computing and IoT. The project and the seminars shall be documented in short reports. The laboratory sessions and, the project are mandatory, and so is preparing and leading at least one seminar.

The examination consists of a written project report, an oral seminar, a written seminar report, and a written exam. The laboratory exercises and the project are mandatory parts of the course. The student also needs to prepare and make at least one seminar presentation to pass the course. The final examination is done by a written exam at the end of the course.

If there are special reasons, the examiner may make exceptions from the specified examination format and allow a student to be examined in another way. Special reasons can e.g. be study support for students with disabilities.

Course evaluation is part of the course. This evaluation offers guidance in the future development and planning of the course. Course evaluation is documented and made available to the students.