Efficient Resource Management for Secure and Low-Latency O-RAN Communication

• URL: http://arxiv.org/abs/2503.07857v1
• Date: Mon, 10 Mar 2025 21:03:48 GMT
• Title: Efficient Resource Management for Secure and Low-Latency O-RAN Communication
• Authors: Zaineh Abughazzah, Emna Baccour, Ahmed Refaey, Amr Mohamed, Mounir Hamdi,
• Abstract summary: Open Radio Access Networks (O-RAN) are transforming telecommunications by shifting from centralized to distributed architectures.<n>O-RAN's reliance on cloud-based architecture and enhanced observability introduces security and resource management challenges.<n> Efficient resource management is crucial for secure and reliable communication in O-RAN, within the resource-constrained environment.
• Score: 6.416635302499242
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Open Radio Access Networks (O-RAN) are transforming telecommunications by shifting from centralized to distributed architectures, promoting flexibility, interoperability, and innovation through open interfaces and multi-vendor environments. However, O-RAN's reliance on cloud-based architecture and enhanced observability introduces significant security and resource management challenges. Efficient resource management is crucial for secure and reliable communication in O-RAN, within the resource-constrained environment and heterogeneity of requirements, where multiple User Equipment (UE) and O-RAN Radio Units (O-RUs) coexist. This paper develops a framework to manage these aspects, ensuring each O-RU is associated with UEs based on their communication channel qualities and computational resources, and selecting appropriate encryption algorithms to safeguard data confidentiality, integrity, and authentication. A Multi-objective Optimization Problem (MOP) is formulated to minimize latency and maximize security within resource constraints. Different approaches are proposed to relax the complexity of the problem and achieve near-optimal performance, facilitating trade-offs between latency, security, and solution complexity. Simulation results demonstrate that the proposed approaches are close enough to the optimal solution, proving that our approach is both effective and efficient.

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