Analysis on Age of Information in Partial Computing Edge Computing Systems with Multi Source-Destination Pairs
Haozhe Li, Guangwei Gong, Jiao Zhang, Haitao Zhao, Li Zhou, Jibo Wei · 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) · 2022
Some Internet of Things (IoT) applications represented by vehicular networks, Internet of Medical Things (IoMT), and fire alarm systems have high requirements on the freshness of receiving information. Due to limited computing capability of IoT devices, mobile edge computing (MEC) is applied to reduce packet calculation time and improve packet freshness. In this paper, we investigate a MEC system for sharing vehicle status information and use the age-of-information (AoI) to define the freshness of information in the MEC system. The whole system is modeled as a two-stage tandem queue model with multi source-destination pairs. We derive the closed-form expression for the average AoI of partial computing and analyze the impact of system parameters on the average AoI, which provides guidance on how to set parameters to maximize the information freshness of the MEC system. As a more flexible scheme, partial computing we used reduces the AoI of the MEC system compared to remote computing. Numerical analysis validates our theory.