REGULATIONS FOR THE MASTER OF COMMERCE DEGREE IN CLOUD COMPUTING AND INTERNET OF THINGS (MCI)

Duration	1½ years
Credit Load	306
Minimum Credit Load	270
Maximum Credit Load	342
Maximum MBKs Credit Load	216
ZNQF Level	9

 

1. PURPOSE OF THE PROGRAMME

Cloud Computing and Internet of Things places emphasis more on the application of computing in distributed environments as the world is globalised and continue to intersect. The program aims to:

• Develop cloud IoT managers and engineers
• Design and develop IoT applications and services adapted to industrial needs
• Manage and analyse data produced by Cloud IoT systems

2. ENTRY REQUIREMENTS

An Honours degree with a degree class of at least 2.1 in Computing (Computer Engineering, Informatics, Information Systems, Computer Science, Software Engineering) or Electronic Engineering or related supported with a strong programming background.

3. PROGRAMME CHARACTERISTICS

Areas of study:

Programming; Cloud Computing; IoT; Emerging Technologies in Cloud IOT; Security and Networking in Cloud IoT

Specialist Focus: The goal of the programme is to help meet the increasing demand for knowledgeable personnel who possess a balanced combination of technical and managerial skills in the field Cloud IOT.

Orientation: Research and innovation oriented. Teaching and learning are professionally oriented and focused on practical aspects

Distinctive Features: The programme is driven so much by the requirements of Professional bodies who demand and expect compliance with the Cloud Computing Association (CCA), Institute of Electrical and Electronics Engineers Computer Society (IEEE CS), Association for Computing Machinery (ACM), International Association of Computer Science and Information Technology (IACSIT). Consultations are made time and again to maintain programme relevance to the ever-changing technological world. The programme builds the research-technology-innovation continuum and focuses on knowledge development and application using a student-centred approach

4. CAREER OPPORTUNITIES AND FURTHER EDUCATION

Careers in Cloud IOT include Managers in Data Science Engineering, Data Analytics, Big Data Consultancy, Data Warehousing, Database Management and Business Intelligence, Scholars and Academia. Doctoral studies in Cloud IOT or in interdisciplinary programmes related to Cloud Computing and Internet of Things and Professional Certifications in related field.

5. PROGRAMME DELIVERY

• Teaching and Learning Methods: Lectures, tutorials, seminars, group work, industrial visits, Work-Related learning, research project, practicals and innovations/ dissertation, and individual independent study.
• Assessment Methods:Written, practical and oral examinations, in-class tests, assignments, presentations, Work-Related learning report, projects and final year research project report.

6. LEARNING OUTCOMES

By the end of the programme a graduate will be able to:

• Describe the IoT and Cloud architectures
• Deploy Cloud Services using different cloud technologies.
• Implement security features to protect data stored in the cloud
• Research, publish, and develop several Cloud IOT based projects
• Gain Knowledge and skill in data analytics which is essential for getting value from IoT

7. GENERAL PROVISIONS

Refer to faculty and general regulations

8. PROGRAMME ASSESSMENT

8.1 Evaluation of students shall normally be based on continuous assessment as well as formal university examinations that are held at the end of each semester.

8.2 Continuous Assessment will account for 40% of the overall assessment. No continuous assessment shall be carried over to the next semester.

8.3 Final examination accounts for60% of the overall assessment.

8.4 The department shall determine which items will be included in the continuous assessment and shall define the relevant weighting to each item.

8.5 To be admitted to the examinations, a candidate must;

8.5.1 be a registered student of the University in accordance with the General Regulations

8.5.2 have satisfactorily attended and completed the approved modules of study.  completion of modules shall require submission of all written assignments and tests that constitute the continuous assessment

8.5.3 have attended and participated in seminars, tutorials and practical classes, presentations and other activities as required by the Department.

8.5.4 Candidates shall be informed in advance of the deadline of submission of dissertation or project. Unless the Academic Board has granted prior permission for an extension of this deadline any candidate who fails to meet this submission deadline shall normally fail the dissertation or project. In such cases, on the recommendation of the Examiners, candidates may be permitted to resubmit the dissertation or project at a later date, normally within three months of the original submission deadline. Unless otherwise determined by Senate, the maximum mark allowed for such work should be 50%

9. PROVISION FOR PROGRESSION

Refer to general and faculty regulations for provision for progression

10. FAILURE TO SATISFY EXAMINERS

Refer to general regulations

11. GRADING AND DEGREE CLASSIFICATION

Refer to general regulations

12. DEGREE WEIGHTING

Refer to faculty regulations

13. AWARD OF DEGREE

Refer to general regulations

 

Level 1 Semester 1

Code Module Description Prerequisites Credits

MCI131 Fundamentals of Cloud IoT 18

MCI132 Programming for Data Science and IOT 18

MCI133 Cloud IOT Systems Management 18

MCI134 Database Technologies for Cloud IoT 18

MCI135 Cloud IOT infrastructure and operating systems 18

 

Level 1 Semester 2

Code Module Description Prerequisites Credits

MCI136 Cloud services and Virtualization 18

MCI137 Research Methods 18

MCI138 Cyber Security in Cloud IOT 18

MCI139 Cloud networks and Internetworking 18

MCI140 Human-Computer interaction 18

 

Level 2 Semester 1

Code Module Description Prerequisites Credits

MC1232 Optimization techniques in Cloud IOT 18

MCI233 Containerization in Cloud IOT 18

MCI231 Dissertation/Research Project 90

MCI234 Emerging Technologies for Cyber-Physical Systems 18

 

• MODULE SYNOPSES

 

MCI 131 Fundamentals of Cloud IoT The module provides an overview of the Internet of Things (IoT) and Cloud Computing concepts, infrastructures and capabilities with emphasis on the architecture and design of IoT systems, the different technologies (wireless/mobile/sensor) governing system implementation, the migration of the data to the Cloud for processing and the commercial and business implications of technical advances in this area

MCI 132 Programming for Data Science and IOT The module covers IOT applications. An IoT system may involve several programs in several different languages. This module covers the following IOT applications SOA Distributed Systems, Artificial Intelligence, Web Sockets and Big Data, Web Stacks and Service Platforms. The applications are supported by several languages that can be used namely C++/C, Swift, Raspbery PI, Block Based languages, Node-RED, LUA, Python, JavaScript, Java and Kotlin.

MCI 133 Cloud IOT Systems Management An appraisal of reasons behind need for Cloud IOT systems management. Considerations of fundamentals of Cloud IOT management and requirements for IOT device management. An integrated approach of systems management in both physical and IT systems audits. Trust-based Cloud IOT service management and Cloud IOT deployment management. The wider IOT ecosystem and associated management challenges.

MCI 134 Database Technologies for Cloud IOT The module is driven towards the latest IOT database technologies. The functionalities and implementation of IOT based databases and IOT database architectures. Enabling technologies for embeddable databases, comparison of Time series and Common database technologies for IOT. Requirements and considerations taken to adopt an IOT database. IOT database modularity and other compliance issues and opportunities and challenges for IOT databases.

MCI 135 Cloud IOT infrastructure and operating systems The module recognizes the evolutionary step of Cloud based IOT. Cloud architecture layers which augment IOT through remote computing and power infrastructure. Cloud IoT infrastructure and OS service characteristics such as increased scalability, automatic deprovisioning, secure integration, Pay-as-you-go, performance monitoring and measuring. Based on IaaS, PaaS and/or SaaS, while maintaining cloud infrastructure convergence.

MCI 136 Cloud services and Virtualization This module provides a hands-on comprehensive study of Cloud concepts and capabilities across the various Cloud service models including IaaS, PaaS, SaaS and BPaaS, how CPU, memory, and I/O resources are virtualized and present real use cases such as Amazon EC2.  Virtualisation will look at evolution of infrastructure migration approaches (virtualization-VMWare/Xen/KVM virtualization, adaptive virtualization, Cloud Computing and on-demand resource provisioning).

MCI137 Research Methods The module covers research, research types, Research planning and design, Project Proposal, Data collection techniques, Literature review, Research techniques, Methodology and Methods, Sampling techniques, Validity and reliability, Research report writing, Ethical issues in Information Systems Research.

MCI 138 Cyber Security in Cloud IOT  The module covers Cloud security concepts, security and protection architectures for cloud and IoT, threat models and attack methodologies for cloud and IoT, security applications and management of cloud and IoT, challenges related to security and privacy for cloud and IoT, cloud security approaches: encryption, tokenization/obfuscation, cloud security alliance standards, cloud security models and related patterns, data analysis of IoT and cloud for security

MIC 139 Cloud networks and internetworking The module covers enabling communication technologies for IoT and cloud, IoT and Cloud Networks, Web services, REST and authorization protocols, Wireless Communication for LANS, PANS and IOT, Network Security and Mechanisms, Mobile & Wireless Networks, Wireless, Sensor & Actuator Networks, Connecting things: lower layers, IPv6, transport protocols, Web of things: REST, MQTT, and CoAP

MIC 140 Human Computer interaction The module covers Principles (Feedback Cycles and Direct Manipulation, Design Principles and Heuristics, Mental Models and Distributed Cognition), Methods (Need finding and Requirements Gathering, Low-Fidelity to High-Fidelity Prototyping, Predictive, Empirical, and Qualitative Evaluation) and Applications (Virtual and Augmented Reality, and others, Ubiquitous and Context-Sensitive Computing, and others, Healthcare, Education, and Security, and others)

MIC 231 Dissertation/Research Project The module is the final year dissertation that involves in-depth research in a particular area of interest in Cloud Computing and IOT. The research findings are expected to be published in peer-reviewed journals or conference proceedings. The deliverable for this module is a dissertation.

MIC 232 Containerization in Cloud IOT The module covers how containerization works, determinants of selection of a platform for containerisation, types of commercial container management solutions, security architecture of containers, containerising applications and managing containers, container models, containerisation in Paas clouds, container orchestration and clustering, engines used by enterprise organizations such as Docker, CoreOS’rkt, Google Kubernete, Amazon AWS and Cloud Foundry

MIC 233Optimization Techniques in Cloud IoT The modules focus on optimization of performance and efficiency of different cloud IOT architectures, comparisons of traditional cloud IOT models to newer models for optimizing performance and efficiency, optimization of energy consumption in IOT applications and cloud resources. It involves assessment of proposed algorithms and deducing their effectiveness in dynamic and heterogeneous environment and adoption algorithms for reducing the energy consumption of task requests.

MCI 234 Emerging Technologies for Cyber Physical Systems This module will cover contemporary issues in relation to emerging technologies that can be used to realise cyber-physical systems. Cyber-Physical Systems (CPS), are collections of physical and software components that communicate and interact with users via networks.