AI-Driven Edge Computing for Intelligent Resource Management in Internet of Things Networks

Author(s)	Mr. Aimn Azoumi Mohammed Ikriam
Country	India
Abstract	The rapid growth of IoT applications has increased the demand for efficient computational resources. Edge computing reduces latency by processing data closer to IoT devices, but limited and heterogeneous edge resources make task management challenging. This study proposes an AI-driven resource management framework for intelligent task allocation in IoT edge environments. The framework analyzes workload and resource conditions, including CPU utilization, memory, latency, bandwidth, and task requirements, to select suitable edge nodes. The proposed approach is evaluated using execution time, latency, energy consumption, resource utilization, task completion rate, and throughput. The study aims to demonstrate that AI-based resource management can improve resource utilization, reduce latency and energy consumption, and enhance the performance of IoT edge computing systems.
Field	Engineering
Published In	Volume 8, Issue 5, September-October 2026
Published On	2026-09-11

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International Journal For Multidisciplinary Research