Title :
Improving the Performance of Network Congestion Control Algorithms
Author :
Xuan Zhang ; Papachristodoulou, A.
Author_Institution :
Dept. of Eng. Sci., Univ. of Oxford, Oxford, UK
Abstract :
This technical note describes a redesign framework for fluid-flow models of network congestion control algorithms. Motivated by the augmented Lagrangian method, we introduce extra dynamics to algorithms resulting from traditional primal-dual methods to improve their performance while guaranteeing stability. We use our method to redesign the primal-dual, primal and dual algorithms for network flow control. In particular, we investigate the influence of the gains resulting from the extra dynamics on system stability and robustness to time delays. We provide a method to improve the transient performance and delay robustness of the overall system by tuning these gains.
Keywords :
delays; flow; large-scale systems; stability; augmented Lagrangian method; dual algorithm; fluid-flow models; large-scale networks; network congestion control algorithms; network flow control; primal algorithm; primal-dual method; system stability; time delays; transient performance; Algorithm design and analysis; Asymptotic stability; Delays; Heuristic algorithms; Radio frequency; Robustness; Stability analysis; Augmented Lagrangian; Lyapunov methods; delay effects; linear robustness; network congestion control;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2014.2336338