Blockchain is a revolutionary technology for constructing trustworthy communications for 6G multiaccess edge computing (6G-MEC). Designing a blockchain-based access control system for 6G-MEC is challenging due to the highly heterogeneous edge devices (EDs) in 6G-MEC. However, traditional blockchain-based access control methods cannot satisfy the heterogeneous device scenarios and are unable to assign voting weights based on the performance of EDs. In this article, we propose a trustworthy access control method for 6G-MEC networks and demonstrate how blockchain can be utilized in our proposed blockchain-assisted multiaccess control approach. Our approach develops an attribute validation and a validation weight method to offer strengthened access control in a decentralized context. We have proposed a trustworthy access control for multiaccess edge computing by using a multitier blockchain architecture and a reinforcement-learning-based weight determination algorithm for ED to eliminate the influence on blockchain consensus behavior. Experimental results demonstrate the effectiveness of our proposed approach.

Artificial Intelligence (AI) technology has been empowered to be a significant driven force within the edge context for powering up contemporary complex systems, such as smart critical infrastructure. Interconnectivity between physical and cyber spaces further introduces the needs of digital twin, which allows AI-based solutions to optimize various tasks in physical operations. However, due to the complexity of the setting in digital twin, task allocation is encountering multiple challenges, such as concurrent meeting the requirements of energy saving, efficiency, and accuracy. In this work, we propose a Digital Twin-Enabled Edge AI (DTE2AI), supported by our Energy-aware High Accuracy Strategy (EAHAS), which focuses on optimizing the training accuracy of AI tasks under the limits of training time and energy consumption. The average of the training accuracy was enhanced 12% based on our experiment evaluations.