Distributed Optimization With Asynchronous Computation and Event-Triggered Communication

• 成果类型: Article
• 署名作者: Dong, Ziwei; Jin, Yaochu; Mao, Shuai; Ren, Wei; Du, Wei; Tang, Yang
• 署名单位: East China University of Science & Technology; Westlake University; Nantong University; University of California System; University of California Riverside
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3449140
• 发表日期: 2025
• 页码: 1084-1099
• 关键词: Optimization; CONVERGENCE; TOPOLOGY; Heuristic algorithms; Directed graphs; computational efficiency; Upper bound; Asynchronous scheme; distributed optimization; Event-triggered scheme; linear convergence rate

摘要

The implementation of distributed optimization, depending on the application, imposes escalating demands on communication and computational synchronization, with the general desire for the robust performance in the face of computationally slow agents and the avoidance of unnecessary communication. In this article, we propose a distributed algorithm with asynchronous computation and event-triggered communication (DAAET) that enables the nodes to flexibly determine their update and information transmission instants. DAAET achieves compatibility with nodes operating at varying computation frequencies and accomplishes a reduction in both wall time and communication costs. Meanwhile, this article proposes a model reconstruction technique to handle disconnectivity arising from the asynchronous implementation of the event-triggered mechanism. Theoretical analysis demonstrates the algorithm's linear convergence to the global optimum under relaxed conditions. The effectiveness and advantages of our approach are demonstrated through a set of examples, showcasing its potential for practical applications.