An Zuoyu, Wu Shaohua, Liu Tiange, Jiao Jian, Zhang Qinyu
Communication Engineering Research Centre, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.
Entropy (Basel). 2021 Jun 4;23(6):714. doi: 10.3390/e23060714.
Cyber-physical systems (CPS) have been widely employed as wireless control networks. There is a special type of CPS which is developed from the wireless networked control systems (WNCS). They usually include two communication links: Uplink transmission and downlink transmission. Those two links form a closed-loop. When such CPS are deployed for time-sensitive applications such as remote control, the uplink and downlink propagation delay are non-negligible. However, existing studies on CPS/WNCS usually ignore the propagation delay of the uplink and downlink channels. In order to achieve the best balance between uplink and downlink transmissions under such circumstances, we propose a heuristic framework to obtain the optimal scheduling strategy that can minimize the long-term average control cost. We model the optimization problem as a Markov decision process (MDP), and then give the sufficient conditions for the existence of the optimal scheduling strategy. We propose the semi-predictive framework to eliminate the impact of the coupling characteristic between the uplink and downlink data packets. Then we obtain the lookup table-based optimal offline strategy and the neural network-based suboptimal online strategy. Numerical simulation shows that the scheduling strategies obtained by this framework can bring significant performance improvements over the existing strategies.
网络物理系统（CPS）已被广泛用作无线控制网络。有一种特殊类型的CPS是从无线网络控制系统（WNCS）发展而来的。它们通常包括两个通信链路：上行链路传输和下行链路传输。这两个链路形成一个闭环。当此类CPS用于诸如远程控制等对时间敏感的应用时，上行链路和下行链路的传播延迟是不可忽略的。然而，现有的关于CPS/WNCS的研究通常忽略了上行链路和下行链路信道的传播延迟。为了在这种情况下实现上行链路和下行链路传输之间的最佳平衡，我们提出了一种启发式框架，以获得能够最小化长期平均控制成本的最优调度策略。我们将优化问题建模为马尔可夫决策过程（MDP），然后给出最优调度策略存在的充分条件。我们提出半预测框架以消除上行链路和下行链路数据包之间耦合特性的影响。然后我们获得基于查找表的最优离线策略和基于神经网络的次优在线策略。数值模拟表明，该框架获得的调度策略相对于现有策略可以带来显著的性能提升。
