Intelligent Reflecting Surface Aided Multi-Tier Hybrid Computing

TL;DR

This paper proposes an IRS-aided multi-tier hybrid computing framework for digital twin edge networks, integrating MEC and DT to enhance system performance, reduce latency, and optimize resource allocation in 6G networks.

Contribution

It introduces a novel IRS-assisted system that converges DT and MEC for the first time, along with an optimization framework to maximize computation rate under constraints.

Findings

IRS significantly improves system performance with proper phase shifts.

The proposed algorithm effectively balances local computing and task offloading.

Simulation confirms the system's ability to enhance real-time monitoring and resource allocation.

Abstract

The digital twin edge network (DITEN) aims to integrate mobile edge computing (MEC) and digital twin (DT) to provide real-time system configuration and flexible resource allocation for the sixth-generation network. This paper investigates an intelligent reflecting surface (IRS)-aided multi-tier hybrid computing system that can achieve mutual benefits for DT and MEC in the DITEN. For the first time, this paper presents the opportunity to realize the network-wide convergence of DT and MEC. In the considered system, specifically, over-the-air computation (AirComp) is employed to monitor the status of the DT system, while MEC is performed with the assistance of DT to provide low-latency computing services. Besides, the IRS is utilized to enhance signal transmission and mitigate interference among heterogeneous nodes. We propose a framework for designing the hybrid computing system, aiming to maximize the sum computation rate under communication and computation resources constraints. To tackle the non-convex optimization problem, alternative optimization and successive convex approximation techniques are leveraged to decouple variables and then transform the problem into a more tractable form. Simulation results verify the effectiveness of the proposed algorithm and demonstrate the IRS can significantly improve the system performance with appropriate phase shift configurations. Moreover, the results indicate that the DT assisted MEC system can precisely achieve the balance between local computing and task offloading since real-time system status can be obtained with the help of DT.