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[2602.13227] An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Trading
Summary
This paper presents an innovative AI control plane for 6G network slice orchestration, emphasizing agentic autonomy and market-aware capabilities for enhanced management and monitoring.
Why It Matters
As 6G networks evolve, traditional methods of network slice orchestration become inadequate. This research proposes a new AI-driven framework that adapts to dynamic environments, showcasing the potential for improved efficiency and decision-making in future network management.
Key Takeaways
- Proposes an agentic AI control plane architecture for 6G networks.
- Integrates market-aware orchestration for dynamic resource management.
- Utilizes natural language interfaces for user interaction with AI functions.
- Demonstrates scalability and adaptability in a real-world testbed.
- Highlights the role of AI in ensuring responsible and explainable network management.
Computer Science > Networking and Internet Architecture arXiv:2602.13227 (cs) [Submitted on 27 Jan 2026] Title:An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Trading Authors:Eranga Bandara, Ross Gore, Sachin Shetty, Ravi Mukkamala, Tharaka Hewa, Abdul Rahman, Xueping Liang, Safdar H. Bouk, Amin Hass, Peter Foytik, Ng Wee Keong, Kasun De Zoysa View a PDF of the paper titled An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Trading, by Eranga Bandara and 11 other authors View PDF HTML (experimental) Abstract:6G networks are expected to be AI-native, intent-driven, and economically programmable, requiring fundamentally new approaches to network slice orchestration. Existing slicing frameworks, largely designed for 5G, rely on static policies and manual workflows and are ill-suited for the dynamic, multi-domain, and service-centric nature of emerging 6G environments. In this paper, we propose an agentic AI control plane architecture for 6G network slice orchestration, monitoring, and trading that treats orchestration as a holistic control function encompassing slice planning, deployment, continuous monitoring, and economically informed decision-making. The proposed control plane is realized as a layered architecture in which multiple cooperating AI agents. To support flexible and on-demand slice utilization, the control plane incorporates market-aware orchestration capabilities, allowing slice requirements, pricing...