Large-scale optimization algorithms for optical and fiber networks

Networks are moving towards being adaptive. This means that automation will be used to replace processes which are today highly manual. This project proposes a development of knowledge in the area of algorithms required to enable adaptive networks. The project will train two PhD students to understand optical networks and devise optimization algorithms in the areas of interest. In particular, the algorithms will be devised to be fast and near-optimal to enable their implementation in the network in accordance with operator’s goals of making the network near-optimal and adaptive. We anticipate that the algorithms will be implemented in the network and used to make transport networks work near-optimality.

Intern: 
Shima Ghaneizare
Faculty Supervisor: 
Brigitte Jaumard;Tristan Glatard
Province: 
Quebec
Partner: 
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