Resource Optimized Network Virtualization Empowered Metaverse for Wireless Networks

Latif U. Khan, Mohsen Guizani, Chang-Dong Wang, Di Wu

Abstract: Metaverse has gained rapid interest from the research community due to its various promising features. These features include proactive learning and self-sustainability. These features enable wireless systems with analysis prior to deployment, efficient resource management with strict latency, and operation with the least possible intervention from the operators. Therefore, deploying the metaverse for wireless systems will offer many benefits. However, metaverse signaling itself requires novel design. Therefore, in this work, a new framework using network virtualization for the metaverse is proposed. Such virtualization will provide more flexibility in terms of management by using the shared physical network resources to support different services. The proposed framework takes into account three key stakeholders, namely, the network operators, a metaverse operator, and the end-users. Resources will be purchased by a metaverse operator from network operators and allocated to users in the proposed framework. To carry out this interaction, a cost function is defined that considers both communication resources and computing resources. By optimizing communication resource management, computing resource management, association, communication resources cost, and computing resource management costs, the cost function is minimized. To achieve this, we propose a strategy based on matching theory and convex optimization. In order to demonstrate the effectiveness of the proposed scheme, numerical results are provided in the final section.