Distributed Composite Optimization Over Relay-Assisted Networks
Chong‐Xiao Shi, Guang‐Hong Yang · IEEE Transactions on Systems Man and Cybernetics Systems · 2020
This article studies the distributed composite optimization problem over relay-assisted networks (DCOP-RNs). By combining the local primal–dual updates with a data fusion strategy, an effective distributed algorithm is developed to solve the DCOP-RN. Compared with the existing linearized alternating direction method of multipliers (ADMMs), this article provides a novel interpretation of the proposed algorithm. More specifically, it is shown that the proposed algorithm can be interpreted as asimplified proximal augmented Lagrangian method. Within this framework, a simplified convergence analysis of the algorithm is conducted, based on which the convergence to an optimal solution to the DCOP-RN is proved. Further, taking into account the limited bandwidth in real networks, this article proposes aquantizeddistributed algorithm to solve the DCOP-RN. Especially, a relationship between the quantization resolution and the convergence accuracy of the algorithm is established. Finally, simulation examples verify the theoretical results.