MPhil in Advanced Computer Science
Information for prospective students of the ACS MPhil.
Introduction to the DTG and our research areas
Please browse the research section of the DTG website for an overview of our research interests.
Faculty members
Dr Alastair Beresford Homepage: http://www.cl.cam.ac.uk/~arb33
Dr Robert Harle Homepage: http://www.cl.cam.ac.uk/~rkh23
Professor Andy Hopper: Homepage: http://www.cl.cam.ac.uk/~ah12/
Dr Andrew Rice Homepage: http://www.cl.cam.ac.uk/~rkh23
Dr Ian Wassell Homepage: http://www.cl.cam.ac.uk/research/dtg/people/?userid=ijw24
Suggested Projects or Project Areas
Computing for the future of the planet
See here for an overview of the project and publications. Students who are interested are welcome to submit project ideas within the four research themes. Some of the current projects relevant to this area are considering understanding and reducing the power consumption of servers (Anthony Hylick), provisioning data centres with renewable energy (Sherif Akoush), low infrastructure location systems (Tom Craig), energy efficient processors (Dr Mbou Eyole-Monono) and sensing using human-reported data and dealing with large, imperfect data sets (Dr Andrew Rice). Please contact Dr Andrew Rice for more information.
Dependable systems
Much of the time it is not possible to construct a 100% reliable system due to resource or operational constraints. Dependable systems are those which monitor and interpret their own performance in order to promote adaption when faults occur. We have considered dependability of location systems (machine vision marker tracking) for Sentient Computing (see: here) and also how acknowledging and adapting to failure can help reduce overprovisioning in our IT infrastructure (see: here). Also of interest is programming and systems-level support for providing dependability. Please contact Dr Andrew Rice for more information.
Privacy and Ubiquitous computing
Ubiquitous computing envisions an era in which computers gather, process and distribute personal information and sensor data. This poses numerous dilemmas of privacy and ethics for individuals and society. Students who are interested in building prototype systems or mathematical models of privacy in this domain should contact Dr Alastair Beresford.
Intelligent Transportation
Motor vehicles provide an ideal platform for mobile sensing. Our investigations in to intelligent transport have included the Sentient Van (see: here) and Dr Alastair Beresford collaborates with other members of the Computer Laboratory on the TIME project and also the cross-institution MESSAGE project. Students who are interested in sensing, mobile systems and data interpretation should contact Dr Alastair Beresford.
Wireless Sensor Networks
The wireless communication team is currently taking part in a couple of large wireless sensor network (WSN) projects; both are being conducted in collaboration with utility companies and both are concerned with infrastructure monitoring. The PIPES project is primarily investigating how to monitor the local water distribution network with the aim of improving leak detection and location while the WINES project is primarily interested in the monitoring of civil infrastructure such as tunnels and bridges. Various opportunities exist to undertake short projects within the context of the multidisciplinary research teams undertaking these projects. We will now briefly describe some potential areas for research projects.
One of our aims is to develop improved WSN planning, deployment and management tools that will be flexible enough to address various network architectures, e.g., star and mesh. They will also be extensible such that they can be applied to both large and small scale WSNs. Network optimization with constraints such as battery life maximization, installation cost minimization or total cost of ownership are of interest.
Propagation measurement and modelling provide the fundamental knowledge required in order to predict the performance of radio networks. Radio channel measurements are central to the determination of accurate empirical path loss models and for the characterisation of signal fading with the use of appropriate probability distribution functions. In addition, the use of Electromagnetic (EM) modelling to predict path loss and signal variability is also being investigated. The determination of novel techniques to reduce the computational burden of such models is of considerable interest.
The use of frequency or space (i.e., antenna) diversity techniques to improve WSN link performance has received little attention to date. Consequently, we would like to develop physical and media access control (MAC) layers that are able to harness the available diversity and so deliver major improvements in WSN link quality.
Interested students should contact Dr. Ian Wassell.
