Optimizing Age of Information in Internet of Vehicles Over Error-Prone Channels

TL;DR

This paper investigates how vehicle mobility and error-prone channels affect the freshness of information in IoV systems, proposing an online optimization method to minimize Age of Information by adjusting data extraction rates.

Contribution

It introduces a novel approach to optimize AoI in IoV considering Doppler shifts and queue models, with a dynamic adjustment algorithm for real-time environments.

Findings

Adjusting data extraction rates significantly reduces AoI.

D/M/1 system achieves lower AoI than M/M/1 in the studied scenario.

Proposed online algorithm effectively adapts to environmental changes.

Abstract

In the Internet of Vehicles (IoV), Age of Information (AoI) has become a vital performance metric for evaluating the freshness of information in communication systems. Although many studies aim to minimize the average AoI of the system through optimized resource scheduling schemes, they often fail to adequately consider the queue characteristics. Moreover, the vehicle mobility leads to rapid changes in network topology and channel conditions, making it difficult to accurately reflect the unique characteristics of vehicles with the calculated AoI under ideal channel conditions. This paper examines the impact of Doppler shifts caused by vehicle speeds on data transmission in error-prone channels. Based on the M/M/1 and D/M/1 queuing theory models, we derive expressions for the Age of Information and optimize the system's average AoI by adjusting the data extraction rates of vehicles (which affect system utilization). We propose an online optimization algorithm that dynamically adjusts the vehicles' data extraction rates based on environmental changes to ensure optimal AoI. Simulation results have demonstrated that adjusting the data extraction rates of vehicles can significantly reduce the system's AoI. Additionally, in the network scenario of this work, the AoI of the D/M/1 system is lower than that of the M/M/1 system.