Grant: Discovery Grants Program - Individual

The research proposal will focus on the development and improvement of optimization methods for solving large scale systems arising in telecommunications and in artificial intelligence. We will conduct theoretical research on the mathematical modeling and the design of efficient solution tools for large scale combinatorial systems. We will also consider particular applications, mainly in the area of communication systems and of artificial intelligence in order to apply the new enhanced tools and validate their efficiency on realistic instances. On the application side of telecommunication networks, we will focus on the development of enhanced tools for network design and management under unicast and multicast traffic. Indeed, with the progressive disappearance of telecommunication monopols and the decreasing cost of the bandwidth (30% per year for several years), the telecommunication industry has encountered deep transformations that led to a much more rational use of the equipment both in the core and the access networks, hence the need of optimization tools for a more efficient management of those networks. Still for the next five years, it is forecast that the traffic in the optical networks will double every year. After a gel of the investments during the last four years, the telecommunication industry is ready to reinvest in the communication infrastructures. A new generation of equipment with new features and better performances is emerging. Both for residential and industrial users, it will allow a better integration of voice, data and video with a more dynamic physical layer. Therefore, the development of efficient tools for the dimensioning of networks becomes more and more important. On the application side in artificial intelligence, the first objective is to generalize the tols previously developed for propositional probabilistic logic to first order probabilistic logic for decidable instances. The second objective is to design efficient solution tools for automated mechanism design and apply them for the self-organization and self-management of overlay networks.