This paper focuses on the distributed online convex optimization problem with time-varying inequality constraints over a network of agents, where each agent collaborates with its neighboring agents to minimize the cumulative network-wide loss over time. To reduce communication overhead between the agents, we propose a distributed event-triggered online primal-dual algorithm over a time-varying directed graph. With several classes of appropriately chose decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. Finally, a numerical simulation example is provided to verify the theoretical results.
@article{arxiv.2311.01957,
title = {Distributed online constrained convex optimization with event-triggered communication},
author = {Kunpeng Zhang and Xinlei Yi and Yuzhe Li and Ming Cao and Tianyou Chai and Tao Yang},
journal= {arXiv preprint arXiv:2311.01957},
year = {2024}
}