Dynamic Slice Resource Management and Information Synchronization Strategy in IoV Based on Digital Twin

To address the low utility of resource management strategy due to diversified user Quality of Service (QoS) requirements and inaccurate information synchronization in Digital Twin Networks (DTN), we propose a dynamic slice resource management and information synchronization strategy in Internet of Vehicles (IoV) based on Digital Twin (DT). First, to realize the dynamic resource allocation between slices and users respectively to adapt to network dynamics, we propose a two-level dynamic resource management strategy based on the DT-assisted slicing architecture of IoV. Second, to guarantee the timeliness of user information transmission and realize the accuracy of the resource management strategy, we propose a DT satisfaction evaluation model including DT mapping granularity, DT timeliness, and resource residual rate to quantify the users’ satisfaction with their DTs association. Finally, we establish a joint optimization model for resource management and DT association to maximize system utility. To address the coupling between strategies, we split the optimization problem into service utility and information synchronization utility subproblems. In the service utility subproblem, we propose a Counterfactual Multi-Agents Twin-Actors Soft Actor-Critic (COMATASAC) algorithm, which can perform slice-level and user-level resource allocation and scheduling actions separately. In the information synchronization utility subproblem, we utilize the Branching Dueling Q-network (BDQ) algorithm to solve the dimensionality explosion problem, and implement the association policy between users’ DTs and servers. Simulation results show that the proposed scheme can effectively reduce the latency and improve the satisfaction of DTs deployment while guaranteeing the QoS.