Adaptive Mirror Descent for the Network Utility Maximization Problem
(2020) 21st IFAC World Congress 2020 — Location: Berlin (12.July.2020)
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- Abstract
- Network utility maximization is the most important problem in network traffic management. Given the growth of modern communication networks, we consider utility maximization problem in a network with a large number of connections (links) that are used by a huge number of users. To solve this problem an adaptive mirror descent algorithm for many constraints is proposed. The key feature of the algorithm is that it has a dimension-free convergence rate. The convergence of the proposed scheme is proved theoretically. The theoretical analysis is verified with numerical simulations. We compare the algorithm with another approach, using the ellipsoid method (EM) for the dual problem. Numerical experiments showed that the performance of the proposed algorithm against EM is significantly better in large networks and when very high solution accuracy is not required. Our approach can be used in many network design paradigms, in particular, in software-defined networks.
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Citations
Ivanova, A., Stonyakin, F., Pasechnyuk, D., Vorontsova, E., & Gasnikov, A. (2020). Adaptive Mirror Descent for the Network Utility Maximization Problem. IFAC-PapersOnLine, 53(2), 7851-7856. https://doi.org/10.1016/j.ifacol.2020.12.1958 (Original work published 2020)