Mutaz Salah Mohamed Osman*

Communication Systems Engineering Department, Sudan University of Science and Technology, Khartoum, Sudan

*Corresponding Author: Mutaz Salah Mohamed Osman, Communication Systems Engineering Department, Sudan University of Science and Technology, Khartoum, Sudan.

Received: August 01, 2025; Published: August 13, 2025

Abstract

As next-generation wireless technologies advance toward sixth-generation (6G) networks, ensuring communication resilience during natural and human-induced disasters has become a key challenge. Traditional infrastructure often fails under extreme conditions due to rigid configurations and lack of real-time adaptability. This paper proposes an AI-driven network slicing architecture designed to maintain communication continuity, prioritize emergency services, and optimize resource utilization in disaster-prone scenarios. By integrating artificial intelligence with 6G slicing mechanisms, the system dynamically reallocates resources, predicts failures, and enhances service availability. Simulation results under various emergency conditions indicate a 43% reduction in service recovery time, latency remaining below 10 milliseconds for high-priority slices, and up to 27% improvement in spectrum efficiency. These findings demonstrate that AI-enhanced slicing can form the backbone of resilient 6G infrastructures capable of supporting life-critical communication services during crises.

Keywords: 6G Networks; Disaster Resilience; Network Slicing; Artificial Intelligence; Edge Computing; Ultra-Reliable Low Latency Communication (URLLC); Service Continuity; Emergency Networks

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Citation

Citation: Mutaz Salah Mohamed Osman. “Resilient AI‑Driven Network Slicing for Disaster‑Aware 6G Infrastructures".Acta Scientific Computer Sciences 7.6 (2025): 11-20.

Copyright

Copyright: © 2025 Mutaz Salah Mohamed Osman. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.