Network Calculus is a theory aiming at computing worst-case bounds on performances in communication networks. The network is usually modelled by a digraph : the servers are located on the nodes and the flows must follow path in the digraph. There are constraints on the trafic curves (how much data have been through a given point since the activation of the network) and on the service curves (how much work each server may provide). To derive bounds on the worst-case performances, as the backlog or the end-to-end delay, these envelopes are combined thanks to tropical algebra operators: min, +, convolution... This thesis focuses on Network Calculus algorithmics, that is how effective is this formalism. This work led us to compare various models in the litterature, and to show expressiveness equivalence between Real-Time Calculus and Network Calculus. Then, we suggested a new (min, +) operator to compute performances bounds in networks with agregated flows and we studied feed-forward networks under blind multiplexing. We showed the difficulty to compute these bounds, but we gave an heuristic, which is polynomial for interesting cases.
