Toward Experience-Driven Traffic Management and Orchestration in Digital-Twin-Enabled 6G Networks
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Abstract (arXiv)
The envisioned 6G networks are expected to support extremely high data rates, low-latency, and radically new applications empowered by machine learning. The futuristic 6G networks require a novel framework that can be used to operate, manage, and optimize its underlying services such as ultra-reliable and low-latency communication, and Internet of everything. In recent years, artificial intelligence (AI) has demonstrated significant success in optimizing and designing networks. The AI-enabled traffic orchestration can dynamically organize different network architectures and slices to provide quality of experience considering the dynamic nature of the wireless communication network. In this paper, we propose a digital twin enabled network framework, empowered by AI to cater the variability and complexity of envisioned 6G networks, to provide smart resource management and intelligent service provisioning. Digital twin paves a way for achieving optimizing 6G services by creating a virtual representation of the 6G network along with its associated communication technologies (e.g., intelligent reflecting surfaces, terahertz and millimeter communication), computing systems (e.g., cloud computing and fog computing) with its associated algorithms (e.g., optimization and machine learning). We then discuss and review the existing AI-enabled traffic management and orchestration techniques and highlight future research directions and potential solutions in 6G networks.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jan 2022.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 1.
3 papers.
- 2022A Bayesian Framework for Digital Twin-Based Control, Monitoring, and Data Collection in Wireless Systemscited by 18
- 2025Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Surveycited by 13
- 2022AI and 6G into the Metaverse: Fundamentals, Challenges and Future Research Trendscited by 8
- 2025Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey3 May 2025
- 2022A Bayesian Framework for Digital Twin-Based Control, Monitoring, and Data Collection in Wireless Systems2 Dec 2022
- 2022AI and 6G into the Metaverse: Fundamentals, Challenges and Future Research Trends23 Aug 2022