Age of Information Analysis in Shared Edge Computing Servers

TL;DR

This paper analyzes the Age of Information in shared edge computing servers, deriving theoretical models for AoI and PAoI under different resource allocation policies to inform robust system design.

Contribution

It introduces a theoretical framework for AoI analysis in MEC servers, considering FIFO and GPS policies, and provides insights for designing resilient resource allocation strategies.

Findings

Derived expected AoI and PAoI distributions for MEC servers.

Compared FIFO and GPS resource allocation policies.

Provided insights on system robustness and design.

Abstract

Mobile Edge Computing (MEC) is expected to play a significant role in the development of 6G networks, as new applications such as cooperative driving and eXtended Reality (XR) require both communication and computational resources from the network edge. However, the limited capabilities of edge servers may be strained to perform complex computational tasks within strict latency bounds for multiple clients. In these contexts, both maintaining a low average Age of Information (AoI) and guaranteeing a low Peak AoI (PAoI) even in the worst case may have significant user experience and safety implications. In this work, we investigate a theoretical model of a MEC server, deriving the expected AoI and the PAoI and latency distributions under the First In First Out (FIFO) and Generalized Processor Sharing (GPS) resource allocation policies. We consider both synchronized and unsynchronized systems, and draw insights on the robust design of resource allocation policies from the analytical results.