This research aimed to develop a Body Area Network using novel ideas from swarm intelligence and, in particular, Ant Colony Optimization. A Body Area Network is a network of sensors (sometimes mobile sensors) outside or inside the human body.  Examples are ‘smart’ clothing where the network is typically a network of sensors recording human body biometric data or for advanced medical monitoring. A system inside the body could be for remote medical sensing, drug delivery, surgery or internal imaging in a distributed way, especially via a mobile ad hoc network such as a horde of nano robots or mobile micro devices.

The project embedded an Ant Colony Optimization algorithm within an existing hybrid mobile ad hoc network developed by the applicant. It was partially tested using Scalable Technologies’ Qualnet network simulator. The Ant Colony Optimization algorithm uses ‘pheromone’ deposits with variable pheromone dispersion rates for active and passive path finding and maintenance analogous to the way ants find optimal paths between the nest and sources of food. This additional layer introduces more network overhead but greater robustness and network reliability.

Outputs

Paper presentations

•  International Symposium of Medical ICT (ISMICT) Conference, 2008
• Sigmobile MobiHoc Annual International Conference, Hong Kong China, May 26-30 2008