SCAN: ML-Based Slice Congestion and Admission Network Controller
Perveen, Abida and Cebecioglu, Berna Bulut and Abozariba, Raouf and Patwary, Mohammad and Aneiba, Adel and Jindal, Anish and Al-Kadri, M. Omar (2025) SCAN: ML-Based Slice Congestion and Admission Network Controller. IEEE Internet of Things Journal. p. 1. ISSN 2372-2541
Preview |
Text
Scan_IEEE.pdf - Accepted Version Download (2MB) |
Abstract
Network slicing enables 5G/6G networks to support Ultra-Reliable Low-Latency Communication (ULLC), enhanced Mobile Broadband (eMBB) and Massive Machine-Type Communication (mMTC). However, while this virtual networking technology enhances network efficiency, it also adds substantial signaling overhead. Maintaining sub-millisecond latency and managing dense deployments require continuous signaling at high resolution, which keeps hardware components active, leading to increased energy consumption. In this paper, we introduce a novel network controller that manages slice congestion and admission, designed to meet flexible Quality-of-Experience requirements for both priority and non-priority traffic. Utilizing metadata from Internet of Things (IoT) device applications and network characteristics, we introduce adaptability and elasticity features, enabled by transfer and reinforcement learning, significantly lowering signaling overhead and network resources. Further, analytical results show the proposed framework effectively reduces rejection rates and congestions across varying mMTC and eMBB traffic loads.
Item Type: | Article |
---|---|
Identification Number: | 10.1109/JIOT.2025.3592803 |
Dates: | Date Event 12 July 2025 Accepted 25 July 2025 Published Online |
Uncontrolled Keywords: | Resource management, Quality of experience, Admission control, Internet of Things, Energy consumption, Transfer learning, Ultra reliable low latency communication, Training, Symbols, Reinforcement learning |
Subjects: | CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science |
Divisions: | Architecture, Built Environment, Computing and Engineering > Computer Science |
Depositing User: | Gemma Tonks |
Date Deposited: | 30 Jul 2025 09:47 |
Last Modified: | 30 Jul 2025 09:57 |
URI: | https://www.open-access.bcu.ac.uk/id/eprint/16545 |
Actions (login required)
![]() |
View Item |