Systematic Analysis of Distributed Optimization Algorithms over Jointly-Connected Networks
Systematic Analysis of Distributed Optimization Algorithms over Jointly-Connected Networks
复制标题
DOI：
10.1109/cdc42340.2020.9303998
复制
发表时间：
2020-03
期刊：
影响因子：
--
通讯作者：
Bryan Van Scoy;Laurent Lessard
中科院分区：
文献类型：
--
作者：
Bryan Van Scoy;Laurent Lessard
我们考虑分布式优化问题，其中一组代理通过与相邻代理通信并执行本地计算来共同优化一个共同目标。对于给定的算法，我们利用鲁棒控制中的工具，系统地分析了通信网络时变情况下的性能。特别是，我们只假设网络在有限的时间范围内联合连接(通常称为B-连通性)，这不需要在每个时刻都连接。当应用于分布式算法DIGing时，我们的界限比文献中提供的界限紧了几个数量级。
We consider the distributed optimization problem, where a group of agents work together to optimize a common objective by communicating with neighboring agents and performing local computations. For a given algorithm, we use tools from robust control to systematically analyze the performance in the case where the communication network is time-varying. In particular, we assume only that the network is jointly connected over a finite time horizon (commonly referred to as B-connectivity), which does not require connectivity at each time instant. When applied to the distributed algorithm DIGing, our bounds are orders of magnitude tighter than those available in the literature.