Module Code: |
H8EFC |
Long Title
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Edge and Fog Computing
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Title
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Edge and Fog Computing
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Module Level: |
LEVEL 8 |
EQF Level: |
6 |
EHEA Level: |
First Cycle |
Module Author: |
Isabel O'Connor |
Departments: |
School of Computing
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Specifications of the qualifications and experience required of staff |
Master’s and/or PhD degree in computing or cognate discipline. May have industry experience also.
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Learning Outcomes |
On successful completion of this module the learner will be able to: |
# |
Learning Outcome Description |
LO1 |
Explore research, frameworks, applications in edge and fog computing. |
LO2 |
Review underlying technologies, limitations, and challenges along with future research direction and discuss generic conceptual framework for optimization problems in fog computing. |
LO3 |
Analyse the restrictions introduced by the General Data Protection Regulation (GDPR), and discuss how these legal constraints affect the design and operation of IoT applications in fog and cloud environments. |
LO4 |
Design and develop simulation scenarios for Edge and Fog Computing using network simulator. |
Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
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No recommendations listed |
Co-requisite Modules
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No Co-requisite modules listed |
Entry requirements |
See section 4.2 Entry procedures and criteria for the programme including procedures recognition of prior learning
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Module Content & Assessment
Indicative Content |
Edge and Fog Computing – Foundations
Internet of Things (IoT) and New Computing Paradigms . Addressing the challenges in Federating Edge Resources
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Edge and Fog Computing – Foundations
Integrating IoT + Fog + Cloud Infrastructures: System Modelling and Research Challenges
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Edge and Fog Computing – Foundations
Management and Orchestration of Network slices in 5G, Fog, Edge and Clouds . Optimization problems in Fog and Edge Computing
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Middleware
Middleware for Fog and Edge Computing: Design Issues . A Lightweight Container Middleware for Edge Cloud Architectures
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Middleware
Data Management in Fog Computing
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Middleware
Predictive analysis to develop to support Fog Application Deployment
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Middleware
Using Machine Learning (ML) for protecting the security and privacy of IoT Systems
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Applications and Issues
Fog Computing Realization for Big Data Analytics. Exploiting Fog Computing in Health Monitoring.
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Applications and Issues
Smart Surveillance Video Stream Processing at the Edge for Real‐Time Human Objects Tracking. Fog Computing Model for Evolving Smart Transportation Applications.
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Applications and Issues
Testing Perspectives of Fog‐Based IoT Applications. Legal Aspects of Operating IoT Applications in the Fog.
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Model & Simulate Edge and Fog computing
Model Fog and Edge Computing Environments Using network simulator toolkit (such as iFogSim, Ns3, OMNeT++, NetSim etc..,)
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Model & Simulate Edge and Fog computing
Simulate Fog and Edge Computing Environments Using network simulator Toolkit (such as iFogSim, Ns3, OMNeT++, NetSim etc..,)
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Assessment Breakdown | % |
Coursework | 40.00% |
End of Module Assessment | 60.00% |
AssessmentsFull Time
Coursework |
Assessment Type: |
Formative Assessment |
% of total: |
Non-Marked |
Assessment Date: |
n/a |
Outcome addressed: |
1,2,3,4 |
Non-Marked: |
Yes |
Assessment Description: Formative assessment will be provided on the in-class individual or group activities. |
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Assessment Type: |
Project |
% of total: |
40 |
Assessment Date: |
n/a |
Outcome addressed: |
4 |
Non-Marked: |
No |
Assessment Description: Model and simulate fog environment scenario that can be simulated through iFogSim. This enables the learner to gain a deep understanding of the edge and fog computing. |
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End of Module Assessment |
Assessment Type: |
Terminal Exam |
% of total: |
60 |
Assessment Date: |
End-of-Semester |
Outcome addressed: |
1,2,3 |
Non-Marked: |
No |
Assessment Description: End-of-Semester Final Examination |
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Reassessment Requirement |
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
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Reassessment Description Repeat examination Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
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NCIRL reserves the right to alter the nature and timings of assessment
Module Workload
Module Target Workload Hours 0 Hours |
Workload: Full Time |
Workload Type |
Workload Description |
Hours |
Frequency |
Average Weekly Learner Workload |
Lecture |
Classroom & Demonstrations (hours) |
24 |
Per Semester |
2.00 |
Tutorial |
Other hours (Practical/Tutorial) |
24 |
Per Semester |
2.00 |
Independent Learning |
Independent learning (hours) |
77 |
Per Semester |
6.42 |
Total Weekly Contact Hours |
4.00 |
Module Resources
Recommended Book Resources |
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Satish Narayana Srirama, Rajkumar Buyya,. (2019), , Fog and Edge Computing : Principles and Paradigms ,Wiley ,.
| Supplementary Book Resources |
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Abdulrahman Yarali,. (2018), , Cloud, Fog, and Edge: Technologies and Trends in Telecommunications Industry (Computer Science, Technology and Applications), Nova Science Pub Inc].
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Mahmood, Zaigham,. (2018), , Fog Computing Concepts, Frameworks and Technologies,Springer.
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Rahmani, A., Liljeberg, P., Preden, J.-S., Jantsch, A.,. (2018), , Fog Computing in the Internet of Things Intelligence at the Edge,Springer.
| This module does not have any article/paper resources |
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This module does not have any other resources |
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