Edge Computing

This subject is available under ICMS undergraduate degrees, please click the button below to find an undergraduate course for you.

Subject Code:

ICT203A

Subject Type:

Core 

Credit Points:

3 credit points 

Pre-requisite/Co-requisite: 

ICT102A Network Fundamentals 

Course level pre-requisite:   A total of 12 credit points including ICT101A, ICT102A, ICT103A, DAT101A from 100 level core subjects prior to enrolling into 200 level subjects. 

Subject Level:

200 

Subject Rationale:

The exponential booming and computing power of Internet of Things (IoT) devices yield a large amount of data which demand more efficient solutions to cater for scalability. Edge computing addresses this need as a more efficient alternative; it is the science of bringing enterprise applications closer to the computing resources in a digital ecosystem by minimising proximity to the data source. The advantage of this reduced proximity is better decision-making capabilities and efficient access to data at its source, which form the basis of this subject.  

This subject equips students with the core concepts, technological insights, and analytical capabilities of edge computing in the organisational decision-making journey. Students will explore how edge computing enables organisations to garner, process, and utilise embedded intelligence in generating corporate value by examining edge computing models and native design, IoT scenarios, edge analytics, and capability-oriented architectures. 

Students will design a small-scale edge-based solution, applying their knowledge of prominent edge computing technologies, platforms, and architectures, including their applications in diverse Industrial IoT (IoT) contexts. They will discover the differences between edge computing and other computing methods, including edge-based security solutions for IoT applications. Future trends and inherent challenges will also be explored in a range of emerging areas. 

Learning Outcomes:

a) Describe edge computing concepts and technologies, including infrastructure components, models, services, and their applications.

b) Analyse an edge ecosystem and identify areas of improvement, demonstrating knowledge of edge-computing architectures and their constituents.

c) Conceptualise and model a basic edge-based solution incorporating security considerations in line with business requirements.

d) Explain the Internet of Things (IoT) service structures and devices in edge computing in diverse industry and Industrial IoT (IIoT) contexts.

e) Analyse the differences and interoperability between edge computing and other computing technologies

Student Assessment:

Broad Topics to be Covered:

Please note that these topics are often refined and subject to change so for up to date weekly topics and suggested reading resources, please refer to the Moodle subject page.