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Network Virtualization Empowered Metaverse: A Hierarchical Matching Approach
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Date
2026
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Abstract
The metaverse has generated significant interest for enabling wireless systems due to its self-sustainability and proactive analytic capabilities. It enables the deployment of meta spaces featuring avatars and digital twins for various real-world applications. However, it has become challenging to efficiently deploy meta spaces on edge/cloud environments while managing communication and computing resources effectively. In this paper, we propose a novel network virtualization framework within a shared system to make the deployment of meta spaces for various metaverse applications cost-efficient. The framework abstracts, isolates, and facilitates the sharing of wireless and computing resources, thereby enhancing flexibility and efficiency for metaverse-driven applications. It involves three key players: network operators (selling resources), metaverse operators (managing transactions), and end-users (purchasing resources). An optimization problem is formulated to optimize the wireless resource allocation, computing resource allocation, association of end-devices with meta spaces deployed at the network operators' base stations, communication resource cost, and computing resource cost. Our problem has a mixed integer non-linear programming (MINLP) problem nature and is difficult to solve using conventional convex optimization. Therefore, we use a decomposition approach and then employ convex optimization and hierarchical matching. Numerical results confirm the validity of the proposed approach.