Gdlcn–dsbo: A Graph Neural Network-driven Multi-objective Framework for Intelligent Cloud Resource Allocation and Task Allocation
This paper proposes Gdlcn–dsbo, a hybrid framework combining Graph-dependent Labelled Convolutional Networks (GDLCN) and Deep Scheduled Butterfly Optimization (DSBO) to optimize multi-objective cloud resource and task allocation, thereby enhancing system efficiency, reducing costs, and ensuring fairness in dynamic IoT environments.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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