Hamayun Khan1,*, Muhammad Atif Imtiaz2, Hira Siddique3, Muhammad Tausif Afzal Rana4, Arshad Ali5, Muhammad Zeeshan Baig6, Saif ur Rehman7, Yazed Alsaawy5
Computer Systems Science and Engineering, Vol.49, pp. 317-331, 2025, DOI:10.32604/csse.2025.061118
- 19 March 2025
Abstract The migration of tasks aided by machine learning (ML) predictions IN (DPM) is a system-level design technique that is used to reduce energy by enhancing the overall performance of the processor. In this paper, we address the issue of system-level higher task dissipation during the execution of parallel workloads with common deadlines by introducing a machine learning-based framework that includes task migration using energy-efficient earliest deadline first scheduling (EA-EDF). ML-based EA-EDF enhances the overall throughput and optimizes the energy to avoid delay and performance degradation in a multiprocessor system. The proposed system model allocates processors… More >
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