Greedy Initialization for Distributed Persistent Monitoring in Network Systems
Greedy Initialization for Distributed Persistent Monitoring in Network Systems
复制标题
网络系统中分布式持久监控的贪婪初始化
DOI：
10.1016/j.automatica.2021.109943
复制
发表时间：
2021
期刊：
影响因子：
6.4
通讯作者：
Cassandras C.G.
中科院分区：
文献类型：
--
作者：
Welikala, S.;Cassandras C.G.
本文考虑了最优的多代理持续监测问题定义为一组代理的一组节点（目标）互连根据固定的网络拓扑结构。我们的目标是控制这个团队，以尽量减少在有限的时间间隔内评估的整体节点状态的不确定性的措施。一类分布式的基于阈值的参数控制器已被提出在以前的工作中，通过强制执行阈值的各个节点状态来控制代理在节点和下一个节点的目的地停留时间。在这种阈值控制策略（TCP）下，使用在线梯度技术来确定最佳阈值。然而，由于问题的非凸性，这种方法往往会导致一个贫穷的局部最优高度依赖于所使用的初始阈值。为了克服这个初始化的挑战，我们开发了一个计算效率离线贪婪技术的基础上的网络系统的渐近分析。然后，该分析用于生成一组高性能的初始阈值。大量的数值结果表明，这样的初始阈值几乎立即（局部）最优或迅速导致最优值。在所有情况下，它们的性能明显优于迄今为止已知的局部最优解。
This paper considers the optimal multi-agent persistent monitoring problem defined for a team of agents on a set of nodes (targets) interconnected according to a fixed network topology. The aim is to control this team so as to minimize a measure of overall node state uncertainty evaluated over a finite time interval. A class of distributed threshold-based parametric controllers has been proposed in prior work to control agent dwell times at nodes and next-node destinations by enforcing thresholds on the respective node states. Under such a Threshold Control Policy (TCP), an on-line gradient technique was used to determine optimal threshold values. However, due to the non-convexity of the problem, this approach often leads to a poor local optima highly dependent on the initial thresholds used. To overcome this initialization challenge, we develop a computationally efficient off-line greedy technique based on the asymptotic analysis of the network system. This analysis is then used to generate a high-performing set of initial thresholds. Extensive numerical results show that such initial thresholds are almost immediately (locally) optimal or quickly lead to optimal values. In all cases, they perform significantly better than the locally optimal solutions known to date.