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Distributed Constrained Optimization With Asynchrony and Delays
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DOI：10.1109/TCSII.2021.3132392.png)
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Abstract
En 中文
This brief investigates a distributed composite optimization problem over an undirected network with equality constraints. The optimization problem includes a smooth term and two possibly non-smooth terms. Most existing results are devoted to developing distributed algorithms in a synchronous setting with a global clock, where the agents cannot proceed to the next iteration until the slowest agent completes its update. A new asynchronous distributed primal-dual forward-backward splitting algorithm (AD-PDFBS) is presented to solve this problem. Each agent can compute and communicate independently at different times, for different durations, with the information it has even if the latest information from its neighbors is not yet available. The convergence of AD-PDFBS is proved by transforming the asynchronous algorithm into a fixed-point problem utilizing the operator splitting scheme under bounded delay assumption. Experiment result confirms the effectiveness of AD-PDFBS.
Keywords:
Optimization
Convergence
Delays
Distributed algorithms
Clocks
Communication networks
Circuits and systems
Asynchronous algorithm
primal-dual algorithm
forward-backward splitting method
non-smooth function
delay
operator splitting scheme
Journal
I
IF:
4.9
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8.8K
Citations:
2.5W