Although wireless networks are becoming a fundamental infrastructure for various control applications, they are inherently exposed to network faults such as lossy links and node failures in environments such as mining, outdoor monitoring, and chemical process control. In this paper, we propose a proactive fault-tolerant mechanism to protect the wireless network against temporal faults without any explicit network state information for mission-critical control systems. Specifically, the proposed mechanism optimizes the multiple routing paths, link scheduling, and traffic generation rate such that it meets the control stability demands even if it experiences multiple link faults and node faults. The proactive network relies on a constrained optimization problem, where the objective function is the network robustness, and the main constraints are the set of the traffic demand, link, and routing layer requirements. To analyze the robustness, we propose a novel performance metric called stability margin ratio, based on the network performance and the stability boundary. Our numerical and experimental performance evaluation shows that the traffic generation rate and the delay of wireless networks are found as critical as the network reliability to guarantee the stability of control systems. Furthermore, the proposed proactive network provides more robust performance than practical state-of-the-art solutions while maintaining high energy efficiency.

尽管无线网络已成为各种控制应用程序的基本基础结构，但它们固有地会遭受网络故障（例如，有损链路和采矿，户外监控和化学过程控制等环境中的节点故障）的影响。在本文中，我们提出了一种主动的容错机制来保护无线网络免受暂时性故障的影响，而无需任何关键任务控制系统的明确网络状态信息。具体而言，所提出的机制优化了多个路由路径，链路调度和流量生成速率，以使其即使遇到多个链路故障和节点故障也能满足控制稳定性要求。主动网络依赖于约束优化问题，其中目标函数是网络的鲁棒性，主要的约束条件是流量需求，链路和路由层需求的集合。为了分析鲁棒性，我们基于网络性能和稳定性边界提出了一种新的性能指标，称为稳定裕度比。我们的数值和实验性能评估表明，流量生成率和无线网络的延迟与网络可靠性一样至关重要，以确保控制系统的稳定性。此外，所提出的主动网络在保持高能源效率的同时，比实际的最新解决方案提供了更强大的性能。基于网络性能和稳定性边界。我们的数值和实验性能评估表明，流量生成率和无线网络的延迟与网络可靠性一样至关重要，以确保控制系统的稳定性。此外，所提出的主动网络在保持高能源效率的同时，比实际的最新解决方案提供了更强大的性能。基于网络性能和稳定性边界。我们的数值和实验性能评估表明，流量生成率和无线网络的延迟与网络可靠性一样至关重要，以确保控制系统的稳定性。此外，所提出的主动网络在保持高能源效率的同时，比实际的最新解决方案提供了更强大的性能。