Optimizing Age Penalty in Time-Varying Networks with Markovian and Error-Prone Channel State.

Yuchao Chen,Haoyue Tang,Jian Song,Jintao Wang

doi:10.3390/e23010091

Abstract

In this paper, we consider a scenario where the base station (BS) collects time-sensitive data from multiple sensors through time-varying and error-prone channels. We characterize the data freshness at the terminal end through a class of monotone increasing functions related to Age of information (AoI). Our goal is to design an optimal policy to minimize the average age penalty of all sensors in infinite horizon under bandwidth and power constraint. By formulating the scheduling problem into a constrained Markov decision process (CMDP), we reveal the threshold structure for the optimal policy and approximate the optimal decision by solving a truncated linear programming (LP). Finally, a bandwidth-truncated policy is proposed to satisfy both power and bandwidth constraint. Through theoretical analysis and numerical simulations, we prove the proposed policy is asymptotic optimal in the large sensor regime.

Highlights

The requirements for data freshness in numerous emerging applications are becoming stricter [1,2]
In [3], it is shown that the optimum packet generation rate of a first-come-first-served (FCFS) system should achieve a trade-off between throughput and delay
We model the effect of data staleness in different scenarios via a class of monotone increasing function related to Age of information (AoI)

Summary

Introduction

The requirements for data freshness in numerous emerging applications are becoming stricter [1,2]. The traditional optimization goals like low delay and high throughput cannot fully characterize the requirement of data freshness. It is necessary to introduce new metrics to capture data freshness in such systems and design strategies to optimize the system performance in the presence of resource and environment restrictions. A popular metric, Age of information (AoI), has been proposed in [3] to measure the data freshness. The optimization of age performance under different systems has been a research hotspot. In [3], it is shown that the optimum packet generation rate of a first-come-first-served (FCFS) system should achieve a trade-off between throughput and delay. Energy constraints are studied in [10,11] to find the trade-off between the age performance and energy consumption. In [11], both offline and online heuristic policies are proposed to optimize the average AoI, which outperform the greedy approach

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Conclusion