Intelligent Edge-Assisted Network Slice Orchestration for Ultra-Reliable Low-Latency Communications in 5G Networks
Keywords:
5G network slicing; edge computing; ultra-reliable low-latency communication; slice orchestration; artificial intelligence; policy governance; resilience; sustainabilityAbstract
The emergence of fifth-generation (5G) wireless systems has introduced a paradigm shift through network slicing, enabling the co-existence of diverse service verticals over a common physical infrastructure. Among the most demanding slice categories is ultra-reliable low-latency communication (URLLC), which necessitates deterministic performance guarantees for mission-critical applications such as autonomous driving, industrial automation, and tele-surgery. However, achieving end-to-end URLLC across geographically distributed edge sites requires a fundamental rethinking of slice orchestration mechanisms that extend beyond centralized resource management. This paper presents a comprehensive system-level analysis of intelligent edge-assisted network slice orchestration for URLLC in 5G networks. We examine the architectural decomposition of orchestration functions across core, edge, and far-edge layers, highlighting the structural trade-offs between centralized coordination and distributed autonomy. The discussion explores how edge intelligence, particularly through machine learning, can enable proactive slice adaptation, predictive fault management, and context-aware policy enforcement. Special attention is devoted to the governance of multi-domain resources, the interplay between computational and networking elements, and the resilience strategies required to sustain URLLC under dynamic conditions. We further evaluate deployment constraints, infrastructure scalability, sustainability considerations, and fairness implications when URLLC slices compete with other service types. The paper contributes a forward-looking perspective on how policy frameworks and standardization efforts can align technical orchestration with socioeconomic objectives. By integrating perspectives from systems engineering, artificial intelligence, and regulatory governance, this work provides a holistic reference for designing and operating next-generation network slices that simultaneously satisfy ultra-reliability and low-latency requirements.
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This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
