An Iterative Interior Point Network Utility Maximization Algorithm
P T Akhil, Rajesh Sundaresan · arXiv (Cornell University) · 2016
Distributed and iterative network utility maximization algorithms, such as the primal-dual algorithms or the network-user decomposition algorithms, often involve trajectories where the iterates may be infeasible. In this paper, we propose a distributed and iterative algorithm that ensures feasibility of the iterates at all times and convergence to the global maximum. A benchmark algorithm due to Kelly et al. [J. of the Oper. Res. Soc., 49(3), 1998] involves fast user updates coupled with slow network updates in the form of additive-increase multiplicative-decrease of suggested user flows. The proposed algorithm may be viewed as one with fast user updates and fast network updates that keeps the iterates feasible at all times. Simulations suggest that our proposed algorithm converges faster than the aforementioned benchmark algorithm.