School of Computer Science

Module 06-25689 (2012)

Mobile & Ubiquitous Computing (Extended)

Level 4/M

Mirco Musolesi Christopher Bowers Semester 2 20 credits
Co-ordinator: Mirco Musolesi
Reviewer: Shishir Nagaraja

The Module Description is a strict subset of this Syllabus Page.


The aims of this module are to:

  • Provide the student with an understanding of the technology used in mobile systems and the constraints that these impose on designers
  • Demonstrate the use of mobile technologies to provide novel services
  • Give students practical and theoretical knowledge and skill in the development of mobile systems

Learning Outcomes

On successful completion of this module, the student should be able to:

  • Demonstrate an understanding of the technologies used in mobile and ubiquitous systems and the constraints that they impose
  • Demonstrate an understanding of the range of novel applications based upon mobile systems as well as their particular requirements
  • Demonstrate an understanding of the models and technologies for developing mobile applications
  • Demonstrate practical skills in developing mobile applications

Teaching methods

2 hr lecture, 1hr tutorial/practical a week


  • Sessional: 2 hr examination (80%), coursework (20%)
  • Supplementary: Examination (80%) with the coursework mark carried forward (20%)

Detailed Syllabus

  1. Introduction to mobile systems design: a. Power, memory, connectivity issues b. System development and programming platforms
  2. Wireless technologies:
    • Wireless communication: radio, medium access protocols
    • Infrastructure networks
    • Infrastructure-free networks: e.g., ad hoc networks, sensor networks, DTNs, opportunistic networks
    • Mobile computing and applications: operating system support for mobility, file systems
  3. Ubiquitous computing: embedded devices, m-commerce, location-aware applications, mobile games and multimedia, the Internet of Things,
  4. Sensing technologies: classes of devices and systems issues, mobile phone sensing systems
  5. Context detection and inference: principles and algorithms for context inference, introduction to machine learning techniques for mobile systems design
  6. Privacy and security issues related to mobile computing
  7. Mobile HCI
    • Design constraints
    • Input, Output
    • Unique affordances of mobile devices
  8. Programming mobile devices
    • The basic building blocks
    • Creating UI’s
    • Locating and Sensing
    • Storing Data
  9. Case studies will be selected among the following:
    • Mobile systems for computational science
    • Mobile sensing systems
    • Mobile technologies for smart cities
    • Pervasive computing at a scale