| AI-Driven Edge Computing for 6G Networks - Hybrid Methodology for AI Lifecycle Management |
| Paper ID : 1062-ICEEM2025 (R1) |
| Authors |
|
Konstantinos Lizos *1, Elena Petrovik2, Saied M. Abd El-atty3 1Engineer in the Hellenic Ministry of Foreign Affairs 2Engineer / Independent Network Consultant & Researcher 3The Dept. of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, 32952, Menouf |
| Abstract |
| 6G wireless networks are promoted on the basis of copying with data-intensive applications with stringent delay and scalable real-time requirements. This paper investigates how combining AI capabilities with edge computing infrastructure creates the foundation for next-generation wireless applications that require immediate response times and distributed intelligence. Our research examines the integrated approach of deploying AI algorithms within edge computing frameworks to support advanced 6G applications, including holographic communications, digital twins, and autonomous systems. We analyze critical technical obstacles related to system scalability, data privacy, security protocols, resource management, and cross-platform compatibility. To overcome AI deployment challenges in edge environments and optimize system performance, we introduce our hybrid methodology namely Orchestrated Adaptive Edge Intelligence (OAEI). This approach demonstrates measurable improvements in processing efficiency and response times. Edge computing infrastructure enables large-scale AI model deployment, facilitating immediate decision-making processes across diverse 6G applications, including autonomous vehicles, smart city systems, extended reality platforms, and industrial IoT networks. Our research provides in-depth analysis of how 6G networks will leverage edge-based artificial intelligence to transform connectivity and computing paradigms. |
| Keywords |
| 6G, Edge Computing, Artificial Intelligence, Machine Learning, Latency, Throughput, Resource Management, Network Slicing, |
| Status: Accepted |