module specification

CS7080 - Cloud Computing and the Internet of Things (2017/18)

Module specification Module approved to run in 2017/18
Module title Cloud Computing and the Internet of Things
Module level Masters (07)
Credit rating for module 20
School School of Computing and Digital Media
Total study hours 200
 
148 hours Guided independent study
52 hours Scheduled learning & teaching activities
Assessment components
Type Weighting Qualifying mark Description
Coursework 15%   Research Presentation (20 minutes)
Coursework 25%   Research Report (2000 words)
Group Coursework 60%   Group Practical Coursework (2500 words + artefact )
Running in 2017/18
Period Campus Day Time Module Leader
Spring semester North Friday Afternoon

Module summary

This module provides students with an in-depth appreciation of the Internet of Things (IoT) and Cloud Computing concepts, models, infrastructures and capabilities. The module will place particular emphasis on modern system architecture and design, key wireless/mobile/sensor technologies, and issues of privacy and trust, in the development of Cloud-based IoT systems. Practical work within the module will provide students with real, hands-on, experience of building a basic Internet of Things infrastructure that can access Cloud Computing services.

Module aims

This module aims to develop knowledge and critical understanding of the underlying principles of Cloud Computing and IoT systems, and the commercial, business and LSEP implications of technical advances in this area. Students will gain practical experience in the development of Cloud-based IoT systems and exposure to appropriate hardware and software platforms that underpin such development.

Syllabus

Cloud Computing and Internet of Things architecture, design, and communication protocols will be covered. This is a rapidly developing area so the following
should be considered as indicative topics only:

1.   Internet of Things (IoT) – Principles, Fundamentals and Business Context
2.   Sensing Technologies - Sensors & Actuators
3.   Machine-to Machine (M2M) Communication
4.   Wireless Technologies – RFID/NFC, Bluetooth/BLE, XBee/ZigBee, Wi-Fi
5.   IoT Messaging Protocols – CoAP, MQTT, REST, AMQP, Websockets
6.   Hardware Development Boards and Software Platforms for IoT
7.   Cloud Computing - Architecture: Infrastructure, Platforms and Software
8.   Cloud Computing – Virtualisation and Resource Management
9.    IoT and Cloud Computing – Application Development and Integration
10.  Security and Privacy for IoT/Cloud Computing
11.  Society and Business Impact of the IoT/Cloud Computing
12.  Current Research within Cloud Computing and IoT

Learning and teaching

The module will be taught by a combination of weekly lectures and workshops, composed of 2 hour lectures and 2 hour workshops each of 11 weeks.  A further 4 hours of study will be associated with the student-led research presentations in Week 12, and another 4 hours with the group coursework presentations/walkthroughs in Week 15. The weekly lecture sessions will be used to explore the main theoretical underpinnings associated with each topic identified in the syllabus, plus indicate suggestions for further study and directed reading [to enable the student to achieve LO1, LO2, LO3, LO5]. The lab-based workshop sessions will draw upon both the students' self-studies and directed learning as well as additional reading of appropriate software documentation, and will provide an opportunity for practical programming instruction and related exercises using appropriate software for the construction of simple Cloud-based, IoT applications [to enable the student to achieve LO4]. It is expected that each student will dedicate approximately 88 hours of independent study to implementing group coursework assignment #1 [LO1, LO2, LO3, LO4, LO5], and a further 60 hours of independent study to researching and producing coursework assignment #2 [LO6, LO7, LO8] and assignment #3 [LO6, LO8].

Learning outcomes

LO1 -  Critically assess the strengths and weaknesses of different IoT system architectures and show understanding of their key features.

LO2 - Evaluate the strengths and weaknesses of different types of Cloud Computing architecture and show understanding of their key features.

LO3 - Demonstrate a critical understanding of key IoT technologies, including (passive and active) sensors, actuators, physical communications layer, message protocols, programming frameworks, and an understanding of energy and bandwidth constraints.

LO4 - Apply extensive hands-on application development skills in building a multi-tiered Cloud-based IoT system.

LO5 - Analyse, appraise and apply knowledge about legal, social, ethical and professional issues related to the design, development, and implementation of Cloud Computing and IoT technologies and systems.

LO6 - Express a critical understanding of current research areas associated with the Internet of Things and Cloud Computing, including an understanding of the commercial context and any privacy/security issues associated with such.

LO7 - Apply broad skill in writing a professional report as a vehicle for communicating ideas in research;

LO8 - Illustrate a comprehensive ability for professional presentation on the subject of their research work;

Assessment strategy

The assessment will be carried out through three courseworks. The first coursework will be group-based (2-3 students per group) and involve the analysis, design, development, and implementation of a prototype, Cloud-based, IoT sensor application (60% of the module mark). The combined second and third coursework (40% of the module mark) consist of an individual research presentation, and an associated written research report, into an agreed student-selected research topic within the Cloud Computing and IoT field of study. The presentations will be class-based and take place in week 12. The module will be passed on the aggregate mark of both coursework assignments.

Details of the assessment components and their matching learning outcomes are indicated below:

Assessment instrument Weight Assessed Learning Outcomes
Coursework (Group-based) 60% LO1, LO2, LO3, LO4, LO5
Research Report 25% LO6, LO7, LO8
Research Presentation 15% LO6, LO8

Re-assessment of groupwork involves individual re-working of the group submission

Bibliography

•   Hwang K., Fox G., Dongarra J., 2011, Distributed and Cloud Computing: Parallel Processing to the Internet of Things, Morgan Kaufmann; 0123858801 [CORE]
 
•   Bahga A., Madisetti V., 2014, Internet of Things – A Hands-on Approach, VPT; 0996025510

•  Chin S., Weaver J., 2015, Raspberry Pi with Java: Programming the Internet of Things (IoT), McGraw-Hill Osborne; 0071842012

•  Tsiatsis V., et al., 2014, From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence, Academic Press Inc; 012407684X