Work

Dynamic Event-Triggered Distributed Online Optimization Subject to Long-Term Constraints

Year: 2026

Type: article

Abstract: This paper investigates distributed online optimization with long-term constraints over time-varying unbalanced multi-agent networks under limited communication resources. To address network imbalance, communication overhead, and the computational burden of per-round constrained projections, a dynamic event-triggered distributed online optimization algorithm with long-term constraints is developed. The algorithm combines an auxiliary-variable-based weighting scheme for column-stochastic networks, a dynamic event-triggered communication protocol, and a long-term constraint mechanism that permits projection onto a simple superset of the original feasible set. We establish bounds on dynamic regret and cumulative absolute constraint violation, both of which explicitly depend on the time horizon and the path variation of the benchmark sequence. Under appropriate parameter choices and sufficiently slow-growing path variation, both bounds are sublinear. Numerical experiments on distributed online linear regression illustrate the theoretical properties of the proposed algorithm.

Source: Mathematics

DOI: 10.3390/math14203728

Authors: Menghui Xiong, Zhixian Chen, Qingyi Liu, Yushun Tan

Institutions: Anhui University, China University of Mining and Technology, Nanjing University of Finance and Economics

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

OpenAlex ID: W7221797291

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