Recent research suggests that modelling social insect behaviour provides a useful basis for solving a wide range of network optimisation problems such as multicast routing, vehicle routing, scheduling problems and sensor networks optimization.

Real ants are capable of finding the shortest path from a food source to the nest using a form of indirect communication, whereby they deposit a chemical trail, known as pheromone, on paths as a guide for other ants. This model can be applied to both a static and dynamic problem where the ants are capable of adapting to changes in the environment.

Initially, this project investigates methods of modelling ant colony behaviour to find efficient solutions to the classic Travelling Salesman Problem. The main objective is then to focus on a telecommunication networks application, in particular the multicast routing problem.

Multicast routing is used to distribute data to multiple recipients over a range of domains, the Internet being the best example. Its main applications include sharing data over peer to peer networks or to broadcast live video and sound for video conferencing.

Dr Marcus Brazil, Talal Al Dhiyebi, Yi-Lun Yap, Avik Chakrabarti