| Optical Burst Switching (OBS) networks are candidates to play an important role in the context of next generation optical networks. In this thesis, we are interested in adaptive routing and quality of service provisioning for these networks.;In the second part of the thesis, we consider the problem of absolute quality of service provisioning for OBS networks where worst-case performance of high priority traffic is guaranteed quantitatively. Particularly, we are interested in the loss-free transmission, inside the OBS network, of high priority bursts, while preserving statistical multiplexing gain and high resources utilization of the OBS network. Also, we aim to improve the performance of best effort traffic. Hence, we propose two approaches: (a) the node-based approach; and (b) the path-based approach. In the node-based approach, we propose to assign a set of wavelengths to each OBS edge node that it can use to send its guaranteed traffic. This assignment takes into consideration physical distances between edge nodes. Furthermore, we propose a wavelength selection algorithm to improve the performance of best effort bursts. In the path-based approach, absolute quality of service provisioning is offered at end-to-end path level. To do this, we propose a routing and wavelength assignment approach which aims to reduce the number of wavelengths required to establish contention free paths. Nevertheless, if this objective cannot be reached because of the limited number of wavelengths in each fiber link, we propose an approach to synchronize overlapping paths without the need for additional equipments for synchronization. Here again, we propose a wavelength selection algorithm for best effort bursts. Numerical results show that both the node-based and the path-based approaches successfully provide absolute quality of service provisioning for guaranteed traffic and improve the performance of best effort traffic. Also, path-based approach could accommodate more guaranteed traffic and improve the performance of best effort traffic compared to node-based approach when the number of wavelengths is sufficient.;Keywords : Optical Burst Switching (OBS); Routing; Wavelength assignment; Wavelength Selection; Reinforcement learning; Combinatorial optimization; Tabu search.;In the first part of the thesis, we study the capability of multi-path routing and alternative routing (deflection routing) to improve the performance of the OBS network proactively for the former and reactively for the latter. In this context, we propose a reinforcement learning-based approach where learning agents, placed in each OBS node, cooperate to learn, continuously, optimal routing paths and alternative paths according to the current state of the network. Numerical results show that the proposed approach improves the performance of the OBS network compared to existing solutions in the literature. |
