This article studies two sensors scheduling with a shared memory channel for remote state estimation in cyber-physical systems (CPSs). We consider that each sensor monitors a plant and sends its local estimate to the remote estimator over a shared memory communication channel, of which the packet reception results between two successive time instants are correlated. This article focuses on how the two sensors are scheduled to minimize the total estimation errors at the remote side. The problem is formulated as the Markov decision process (MDP) and the optimal policy is derived. Moreover, the threshold structure of the optimal policy is given to reduce computation overhead. After proving the Whittle indexability of the overall system under a given condition, the Whittle index policy is adopted to further reduce the computation overhead. Numerical simulations are given to illustrate the theoretical results.

中文翻译：

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网络物理系统环境下共享内存通道的两个传感器远程状态估计调度


本文研究了两个具有共享内存通道的传感器调度，用于网络物理系统 (CPS) 中的远程状态估计。我们认为每个传感器监视一个植物并通过共享内存通信通道将其本地估计发送到远程估计器，其中两个连续时刻之间的数据包接收结果是相关的。本文重点介绍如何安排两个传感器以最大限度地减少远程端的总估计误差。该问题被表述为马尔可夫决策过程（MDP）并导出最优策略。此外，给出了最优策略的阈值结构以减少计算开销。在证明了给定条件下整个系统的Whittle可索引性后，采用Whittle索引策略进一步降低计算开销。给出了数值模拟来说明理论结果。