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Network Virtualization Empowered Metaverse: A Hierarchical Matching Approach
Khan, Latif U. Guizani, Mohsen Yaqoob, Ibrar Al-Fuqaha, Ala Erbad, Aiman Han, Zhu
Khan, Latif U.
Guizani, Mohsen
Yaqoob, Ibrar
Al-Fuqaha, Ala
Erbad, Aiman
Han, Zhu
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Department
Machine Learning
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Type
Journal article
Date
2025
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Language
English
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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.
Citation
L. U. Khan, M. Guizani, I. Yaqoob, A. Al-Fuqaha, A. Erbad and Z. Han, "Network Virtualization Empowered Metaverse: A Hierarchical Matching Approach," in IEEE Transactions on Network Science and Engineering, doi: 10.1109/TNSE.2025.3588451
Source
IEEE Transactions on Network Science and Engineering
Conference
Keywords
Convex optimization, Internet of Things, matching theory, metaverse, network virtualization
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Publisher
IEEE