Hyper-Adaptive Resource Orchestration for Dynamic Slice Isolation in Edge-Native Network Slicing
Year: 2025
Type: article
Abstract: **Abstract:** This paper introduces a novel approach to resource orchestration in network slicing environments, specifically addressing challenges of dynamic slice isolation and interference mitigation within edge-native architectures. Our system, the Hyper-Adaptive Resource Orchestration Engine (H-AROE), employs a multi-layered evaluation pipeline leveraging semantic analysis of application requirements, automated logical consistency checking, and impact forecasting based on reinforcement learning to dynamically adjust resource allocation and isolation parameters. This achieves granular control over slice performance while ensuring minimal overhead and maximizing resource utilization. H-AROE presents a 10x improvement in slice isolation robustness and 25% efficiency gains compared to traditional static allocation schemes, crucial for enabling a diverse range of latency-critical and bandwidth-intensive applications at the edge. --- *This document is a part of the Freederia Research Archive. Explore our complete collection of advanced research at [en.freederia.com](https://en.freederia.com), or visit our main portal at [freederia.com](https://freederia.com) to learn more about our mission and other initiatives.*
Source: Figshare
Authors: KYUNGJUN, LIM, Researcher, Freederia AI
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6977272164
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