Stochastic Event-Triggered Algorithm for Distributed Convex Optimisation

This paper investigates the problem of distributed convex optimisation under constrained communication. A novel stochastic event-triggering algorithm is shown to solve the problem asymptotically to any arbitrarily small error without exhibiting Zeno behaviour. A systematic design of the stochastic e...

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Bibliographic Details
Published in:IEEE transactions on control of network systems Vol. 10; no. 3; pp. 1 - 12
Main Authors: Tsang, Kam Fai Elvis, Huang, Mengyu, Shi, Ling, Johansson, Karl Henrik
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.09.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Convexity
Distributed Optimisation
Event-Triggered Control
Networked Control Systems
Optimization
ISSN:2325-5870, 2372-2533
Online Access:Get full text
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Summary:This paper investigates the problem of distributed convex optimisation under constrained communication. A novel stochastic event-triggering algorithm is shown to solve the problem asymptotically to any arbitrarily small error without exhibiting Zeno behaviour. A systematic design of the stochastic event processes is then derived from the analysis on optimality and communication rate with the help of a meta-optimisation problem. Lastly, a numerical example on distributed classification is provided to visualise the performance of the proposed algorithm in terms of convergence in optimisation error and average communication rate with comparison to other algorithms in the literature. We show that the proposed algorithm is highly effective in reducing communication rates compared with algorithms proposed in the literature.
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ISSN:2325-5870
2372-2533
DOI:10.1109/TCNS.2022.3229769