Large Scale Optimization with Applications in Communication Networks

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My research program deals with theoretical research on large scale optimization methods with applications to different engineering problems arising in communication networks and artificial intelligence. It is built upon some of the results obtained in the previous 6 years, with some involving national or international collaborations. There are three research axes: (i) theoretical advances on decomposition methods and meta-heuristics; (ii) applications to problems arising in communication networks such as the design of mixed-line-rate optical networks, energy-efficient designs and management through, e.g., energy-efficient and survivable logical topologies, provisioning of multicast traffic and (iii) applications in artificial intelligence. The first axis is motivated by the need to solve ever larger optimization problems, with guarantees on the quality of the generated solutions. The applications of the second axis are related to the continued growth of Internet traffic, and the steady increase in the usage of on-demand applications which leads to challenging optimization problems in communication networks. Solutions always need to take into account the capacity limits for some of the existing technology (e.g., processing speed of the electronic routers vs. amount of the traffic to be switched/routed). As well, energy consumption must be tamed in order to avoid unsustainable power requirements in the next coming years. Indeed, the rate of advances in technological and operational efficiency must increase faster than the rate of traffic growth. In terms of operational efficiency, we propose to optimize the design and management of mixed-line rate networks, to enhance the bandwidth usage in order to reduce the energy consumption, and to optimize the provisioning and the protection of the multicast traffic.