Optimization Based Flow Control with Improved Performance∗

Optimization based flow control has been proposed in [2] to improve the network performance with congested bottle links. This rate-based technique has advantages over traditional window based heuristic algorithms in that the optimal performance in terms of maximal aggregate utility function can be achieved when each source adaptively adjusts its data rate. Several decentralized optimization algorithms have been applied to the flow control. However, one of most important features of these algorithms: the relation between the convergence speed and network parameters is not well studied, experimentally or theoretically. The contribution of this paper is two-fold. The first contribution is that we propose Aitken-extrapolation to accelerate the convergence process. Secondly, we compare the convergence speed of various algorithms by theoretic analysis and simulations. Based on the results, the network parameters can be appropriately chosen to improve network performance.