Title: Distributed averaging for accuracy prediction in networked systems Show Chinese title

Title: 网络化系统中准确度预测的分布式平均方法

Abstract: Distributed averaging is among the most relevant cooperative control problems, with applications in sensor and robotic networks, distributed signal processing, data fusion, and load balancing. Consensus and gossip algorithms have been investigated and successfully deployed in multi-agent systems to perform distributed averaging in synchronous and asynchronous settings. This study proposes a heuristic approach to estimate the convergence rate of averaging algorithms in a distributed manner, relying on the computation and propagation of local graph metrics while entailing simple data elaboration and small message passing. The protocol enables nodes to predict the time (or the number of interactions) needed to estimate the global average with the desired accuracy. Consequently, nodes can make informed decisions on their use of measured and estimated data while gaining awareness of the global structure of the network, as well as their role in it. The study presents relevant applications to outliers identification and performance evaluation in switching topologies. Show Chinese abstract

Abstract: 分布式平均是最相关的协同控制问题之一，应用于传感器和机器人网络、分布式信号处理、数据融合和负载平衡。 共识和播客算法已在多智能体系统中得到研究并成功部署，以在同步和异步环境中执行分布式平均。 本研究提出了一种启发式方法，在分布式环境下估计平均算法的收敛速率，依赖于局部图度量的计算和传播，同时涉及简单的数据处理和小消息传递。 该协议使节点能够预测估计全局平均所需的时间（或交互次数）以达到所需的精度。 因此，节点可以在使用测量和估计数据时做出明智的决策，同时了解网络的全局结构及其在其中的角色。 该研究展示了在切换拓扑中异常值识别和性能评估的相关应用。