计算机科学
计算
估计员
信息物理系统
调度(生产过程)
架空(工程)
频道(广播)
马尔可夫过程
网络数据包
马尔可夫决策过程
实时计算
国家(计算机科学)
马尔可夫链
分布式计算
计算机网络
数学优化
算法
数学
机器学习
操作系统
统计
出处
期刊:IEEE transactions on cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2023-04-01
卷期号:53 (4): 2225-2235
被引量:4
标识
DOI:10.1109/tcyb.2021.3112677
摘要
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.
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