Age-Driven Joint Sampling and Non-Slot Based Scheduling for Industrial Internet of Things  

作　　者：Cao Yali Teng Yinglei Song Mei Wang Nan 

机构地区：[1]School of Electronic Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China

出　　处：《China Communications》2024年第11期190-204,共15页中国通信（英文版）

基　　金：supported in part by the National Key R&D Program of China(No.2021YFB3300100);the National Natural Science Foundation of China(No.62171062)。

摘　　要：Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors.Quantifying the data freshness through age of information(AoI),in this paper,we jointly design sampling and non-slot based scheduling policies to minimize the maximum time-average age of information(MAoI)among sensors with the constraints of average energy cost and finite queue stability.To overcome the intractability involving high couplings of such a complex stochastic process,we first focus on the single-sensor time-average AoI optimization problem and convert the constrained Markov decision process(CMDP)into an unconstrained Markov decision process(MDP)by the Lagrangian method.With the infinite-time average energy and AoI expression expended as the Bellman equation,the singlesensor time-average AoI optimization problem can be approached through the steady-state distribution probability.Further,we propose a low-complexity sub-optimal sampling and semi-distributed scheduling scheme for the multi-sensor scenario.The simulation results show that the proposed scheme reduces the MAoI significantly while achieving a balance between the sampling rate and service rate for multiple sensors.

关 键 词：Age of Information(AoI) Industrial Internet of Things(IIoT) Markov decision process(MDP) time sensitive systems URLLC 

分 类 号：TN929.5[电子电信—通信与信息系统] TP393[电子电信—信息与通信工程]