The interconnected smart devices and industrial internet of things devices require low-latency communication to fulfill control objectives despite limited resources. In essence, such devices have a time-critical nature but also require a highly accurate data input based on its significance. In this paper, we investigate various coordinated and distributed semantic scheduling schemes with a data significance perspective. In particular, novel algorithms are proposed to analyze the benefit of such schemes for the significance in terms of estimation accuracy. Then, we derive the bounds of the achievable estimation accuracy. Our numerical results showcase the superiority of semantic scheduling policies that adopt an integrated control and communication strategy. In essence, such policies can reduce the weighted sum of mean squared errors compared to traditional policies.

翻译：互联智能设备与工业物联网设备在资源受限的条件下，需通过低时延通信实现控制目标。本质上，此类设备具有时间关键性特征，同时需基于数据重要性获取高精度输入。本文从数据重要性角度出发，研究多种协调式与分布式语义调度方案，并提出新型算法以分析此类方案在估计精度中的重要性收益。随后推导了可达估计精度的理论界。数值结果表明，采用控制与通信集成策略的语义调度策略具有优越性——与传统策略相比，此类策略可降低加权均方误差总和。