Fairness-aware Latency Minimisation in Digital Twin-aided Edge Computing with Ultra-Reliable and Low-Latency Communications: A Distributed Optimisation Approach

The advanced development of communication technologies and computing platforms open opportunities to enable a wide range of time-sensitive services. However, designing an effective optimisation solution to deal with joint communication and computation resources is a challenging research direction. This paper addresses a fairness-aware latency minimisation problem in the digital twin (DT) aided edge computing with ultra-reliable and low latency communications (URLLC). The optimal solution is obtained by jointly optimising various variables, namely, bandwidth allocation, transmit power, task offloading policies, and the processing rate of user equipment (UE) and edge server (ES). The formulated optimisation problem is highly complicated with many non-convex constraints and strong coupling variables. To deal with the problem, we propose a distributed optimisation solution based on the global consensus approach and the successive convex approximation framework (SCA). Selected numerical results are provided to validate the proposed solution in terms of minimise latency as well as improved fairness among all UEs in the DT network.