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• W4285298311 abstract "Smart factory is an amalgamation of the Industrial Internet of things (IIoT) connecting devices to expedite the production process and delivery of customized products. However, the quest to provision reliable, self-sufficient, and real-time services to smart factory production processes is ever fallowed. To this aim, establishment of a reliable solution for efficient resource utilization, load balancing and task scheduling has become a de-facto necessity. This paper presents an enhanced learning to task scheduling mechanism based on task Criticality and Collapse Aware Scheduling algorithm (CCAS) for efficient resource load-balancing and task management in smart factory. The proposed predictive task scheduling mechanism is developed using ensemble prediction model based on Gradient Boosting Decision Tree (GBDT) because of their exceptional performance, memory efficiency and robustness.The proposed ensemble learning framework provides high level feature abstraction by learning the task parameters to predict task status and machine utilization. A learning-assisted scheduling model is constructed for fair allocation of resources to consummate production maximization for constrained smart manufacturing machine networks. The experimental results demonstrate that the proposed CCAS system significantly improved the smart factory’s performance compared to baseline Rate-monotonic approach. The results verified that proposed enhanced scheduling mechanism yields superior performance in terms of reduced task dropout and starvation rates than the conventional RM method. The developed enhanced predictive RM scheduling improved task dropout and starvation rate by 8% and 7% respectively, compared to the baseline scheduling approach. Furthermore, the proposed scheduling mechanism significantly improved the smart factory resource load balance by provisioning faster response time, decreased task starvation rate and latency and maximized smart machine utilization." @default.
• W4285298311 created "2022-07-14" @default.
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• W4285298311 date "2022-01-01" @default.
• W4285298311 modified "2023-09-25" @default.
• W4285298311 title "A Criticality-Aware Dynamic Task Scheduling Mechanism for Efficient Resource Load Balancing in Constrained Smart Manufacturing Environment." @default.
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• W4285298311 doi "https://doi.org/10.1109/access.2022.3173157" @default.
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