Constraint Games for stable and optimal allocation of demands in SDN

Anthony Palmieri (1, 2) , Arnaud Lallouet (1, 2) , Luc Pons (3, 2)

1 Equipe CODAG - Laboratoire GREYC - UMR6072
2 Huawei Technologies France
3 IRIT-SMAC - Systèmes Multi-Agents Coopératifs

Software Defined Networking (or SDN) allows to apply a centralized control over a network of commuters in order to provide better global performances. One of the problem to solve is the multi-commodity flow routing where a set of demands have to be routed at minimum cost. In contrast with other versions of this problem, we consider here problems with congestion that change the cost of a link according to the capacity used. We propose here to study centralized routing with Constraint Programming and selfish routing with Constraint Games. Selfish routing is important for the perceived quality of the solution since no user is able to improve his cost by changing only his own path. We present real and synthetic benchmarks that show a good scalability.

Domaines: Intelligence artificielle [cs.AI]

Anthony Palmieri, Arnaud Lallouet, Luc Pons. Constraint Games for stable and optimal allocation of demands in SDN. 22 Int. Joint Conf. Artificial Intelligence {IJCAI}, 2019, Macao, China. ⟨hal-02116826⟩