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Non-Fungible Token Enabled Resource Trading Marketplace for 6G Network Slicing

Weerasinghe, Nisita; Porambage, Pawani; Braeken, An; Liyanage, Madhusanka; Ylianttila, Mika (2025-05-05)

 
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https://doi.org/10.1109/CCNC54725.2025.10975970

Weerasinghe, Nisita
Porambage, Pawani
Braeken, An
Liyanage, Madhusanka
Ylianttila, Mika
IEEE
05.05.2025

N. Weerasinghe, P. Porambage, A. Braeken, M. Liyanage and M. Ylianttila, "Non-Fungible Token Enabled Resource Trading Marketplace for 6G Network Slicing," 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, 2025, pp. 1-6, doi: 10.1109/CCNC54725.2025.10975970

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doi:https://doi.org/10.1109/ccnc54725.2025.10975970
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https://urn.fi/URN:NBN:fi:oulu-202505083188
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Abstract

The shift from fifth generation (5G) to sixth generation (6G) networks is anticipated to significantly advance network slicing. This progress is driven by the growing demand for next-generation applications and services. However, these advancements must be managed within the constraints of limited resources. This evolution opens up opportunities for resource sharing through emerging marketplaces, yet it introduces various business and technical complexities that need to be addressed. Additionally, finding cost-effective solutions is also essential for the future of networks. In this paper, we propose a blockchain-based architecture that utilizes non-fungible tokens (NFTs) for the trading of network resources within the 6G network slicing. To the best of our knowledge, this is the first study to represent network resources as NFTs within the context of network slicing. The architecture employs NFTs to authenticate and manage various network resources, providing a decentralized platform for their secure creation, management, and exchange. Using resource NFTs, our system ensures more granular and flexible control over network resources than existing state-of-the-art systems, where NFTs are tied to network slices. We implemented a prototype of this system to validate its viability. Our performance evaluation confirms that the proposed approach is efficient and cost-effective compared to baseline models in managing network resources within network slicing. These findings highlight the potential of our system to transform network management practices and effectively meet the demands of future networks.
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