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  • Published Subscription Original Research

    Machine Learning-Based Task Scheduling and Resource Optimization in Edge-IoT Systems

    Abstract: The rapid expansion of Internet of Things (IoT) applications has introduced significant challenges in managing computational workloads across distributed edge environments. Edge- IoT systems are characterized by limited computational capacity, dynamic task arrivals, and strict latency constraints. Traditional heuristic-based scheduling techniques often fail to adapt to fluctuating workloads and heterogeneous resource availability. This study proposes a machine learning-based task scheduling and resource optimization framework for Edge-IoT systems. The proposed model …

    Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article

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