ksparsh443 / dtwin_ml_model

Implementing Digital twin over AI/ML on 6g Network

DTWIN_ML_MODEL

Implementing Digital twin over AI/ML on 6g Network The deployment of digital twin technology in 6G networks presents a new frontier for the application of AI and ML techniques. Edge association and adaptive edge association can significantly enhance the functionality of digital twins in 6G networks by enabling seamless data transfer between digital twins and real-world objects and systems, thereby enhancing the accuracy and reliability of digital twins. Digital twin transfer can be optimized using AI/ML to reduce latency and improve network efficiency. However, ensuring the security and privacy of digital twin data and developing efficient AI/ML algorithms that can operate within the limited computational and power resources of edge devices are major challenges. In this paper, the authors propose a reliable digital twin-based 6G edge network recovery framework using Blockchain technology, Transfer Learning techniques to improve performance and ensure data privacy and security.