Wireless sensor networks

Project description

Wireless sensor networks (WSNs) are an exciting new technology that lies at the intersection of communication networks and smart monitoring. It is easy to imagine the benefits of a system consisting of hundreds or even thousands of sensors distributed over a region or an object and able to measure any of a multitude of aspects of their environment. In general the sensors communicate their results to other sensors via multi-hop paths and also pass their data to central nodes for intelligent processing. The applications are countless: bushfire early detection, smart-home systems, battlefield surveillance, animal population tracking, and environmental pollution monitoring – to name just a few.

Although WSNs are already extensively utilised in the real word, their full potential remains largely untapped. In contrast to other types of communication networks, sensor network technology is severely limited by battery efficiency. This is because WSNs are required to be autonomous for as long as possible, as they are often deployed in remote, harsh, or even hostile environments.

The topology of the network (i.e., the overall pattern formed by the communication links between pairs of sensors) and the relative locations of the sensors play a large role in the efficiency of the network. This project will therefore focus on the optimisation of any aspect of the topological design phase of WSN deployment. A PhD student can choose to focus on aspects of any of the following design stages: the development of mathematical tools to model and understand optimal WSN deployments, the application of these tools to the construction of new algorithms, or the performance analysis of algorithms by mathematical means and/or by coding the algorithms and performing simulations.

Project team

Leader: Doreen Thomas

Staff: Marcus Brazil, Charl Ras

Other projects

Networks and data in society projects


Electrical & Electronic Engineering,Mechanical Engineering


Networks and data in society


optimization; sensor networks