基于可靠高效的6G边缘网络的数字孪生驱动区块链

Mehmet Ozgen Ozdogan, Levent Çarkacioglu, B. Canberk
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引用次数: 5

摘要

随着无线通信智能设备的快速发展,第五代(5G)移动网络对高数据速率、低延迟、高可用性的需求有限。第六代(6G)移动网络可以使用数字孪生(DT)技术来满足这些需求。DT是物理方面(如6G边缘节点)的虚拟表示。DT使用人工智能(AI),特别是机器学习(ML)算法优化6G边缘节点参数。然而,人工智能和机器学习带来了隐私和安全问题。因此,在6G边缘网络恢复和扩展阶段,必须保护用户数据不被未经授权的人使用。在本文中,我们提出了一种基于区块链技术的可靠的基于数字孪生的6G边缘网络恢复框架。我们应用迁移学习(TL)技术来提高我们提出的框架的性能。我们使用TL和区块链技术确保数据隐私和安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital Twin Driven Blockchain Based Reliable and Efficient 6G Edge Network
With the rapid development of intelligent devices in wireless communication, the fifth generation (5G) mobile networks have limited high data rates, low latency, high avail-ability demands. The sixth-generation (6G) mobile network can use Digital-twin (DT) techniques to meet these demands. DT is the virtual representation of physical aspects such as 6G edge nodes. DT optimize the 6G edge nodes parameters using artificial intelligence (AI) and especially machine learning (ML) algorithms. However, AI and ML bring along privacy and security concerns. Therefore, user data must be protected from unauthorized persons during the 6G edge network recovery and expansion phases. In this paper, we proposed a new reliable Digital Twin-based 6G edge network recovery framework using Blockchain technology. We applied the Transfer Learning (TL) technique to improve our proposed framework’s performance. We ensured data privacy and security using TL and Blockchain.
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