“Age of Information” is a newly introduced metric, getting vivid attention for measuring the freshness of information in real-time networks. This parameter has evolved to guarantee the timely reception of information from the latest status update received by a user from any real-time application. In this paper, we study a centralized, closed-loop, networked controlled industrial wireless sensor–actuator network for cyber–physical production systems. Here, we jointly address the problem of transmission scheduling of sensor updates and the restoration of an information flow-line after any real-time update, having hard-deadline, drops from it, resulting in a break in the loop. Unlike existing real-time scheduling policies that only ensure timely updates, this work aims to accomplish both the time-sensitivity and data freshness in new and regenerative real-time updates in terms of the ‘age’ of information. Here, the coexistence of both cyber and physical units and their individual requirements for providing the quality of service to the system, as a whole, seems to be one of the major challenges to handle. In this work, minimization of staleness of the time-critical updates to extract maximum utilization out of its information content and its effects on other network performances are thoroughly investigated. A greedy scheduling policy called “Deadline-aware Highest Latency First” has been used to solve this problem; its performance optimality is proved analytically. Finally, our claim is validated by comparing the results obtained by our algorithm with those of other popular scheduling policies through extensive simulations.

“信息时代”是一个新引入的指标，在实时网络中衡量信息的新鲜度方面引起了广泛关注。此参数已发展为可以保证及时接收用户从任何实时应用程序接收到的最新状态更新中的信息。在本文中，我们研究了用于网络物理生产系统的集中式，闭环，网络控制的工业无线传感器-执行器网络。在这里，我们共同解决传感器更新的传输调度问题和任何实时更新后恢复信息流线的问题，这些更新具有硬性的最后期限从其下降，从而导致循环中断。与仅确保及时更新的现有实时调度策略不同，这项工作旨在根据信息的“时代”在新的和可再生的实时更新中实现时间敏感性和数据新鲜度。在这里，网络和物理单元的共存以及它们为系统提供服务质量的整体要求似乎是要处理的主要挑战之一。在这项工作中，彻底研究了对时间要求严格的更新的陈旧性最小化，以从其信息内容中提取最大利用率，以及对其他网络性能的影响。贪婪的调度策略称为“最后期限感知的最高延迟优先”已用于解决此问题。通过分析证明了其最佳性能。最后，通过广泛模拟，将我们的算法获得的结果与其他流行的调度策略的结果进行比较，验证了我们的主张。