Energy efficient task scheduling for heterogeneous multicore processors in edge computing
Abstract Edge computing faces challenges in energy-efficient task scheduling for heterogeneous multicore processors (HMPs). Existing solutions focus on reactive workload adaptation and energy prediction but fail to effectively integrate dynamic voltage and frequency scaling (DVFS). This paper propos...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-92604-6 |
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| _version_ | 1849737703326744576 |
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| author | Yanchun Liu Hongxue Qu Shuang Chen Xuejun Feng |
| author_facet | Yanchun Liu Hongxue Qu Shuang Chen Xuejun Feng |
| author_sort | Yanchun Liu |
| collection | DOAJ |
| description | Abstract Edge computing faces challenges in energy-efficient task scheduling for heterogeneous multicore processors (HMPs). Existing solutions focus on reactive workload adaptation and energy prediction but fail to effectively integrate dynamic voltage and frequency scaling (DVFS). This paper proposes a novel algorithm integrating task prioritization, core-aware mapping, and predictive DVFS. Our approach outperforms state-of-the-art methods, reducing energy consumption by 20.9% while maintaining a low 2.4% deadline miss rate. Experiments on real HMP platforms demonstrate the algorithm’s scalability and adaptability to varying workloads. This work advances energy-efficient edge computing, balancing performance and power constraints. |
| format | Article |
| id | doaj-art-48f5dd304ff74347bb6da2248695abe2 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-48f5dd304ff74347bb6da2248695abe22025-08-20T03:06:51ZengNature PortfolioScientific Reports2045-23222025-04-0115112510.1038/s41598-025-92604-6Energy efficient task scheduling for heterogeneous multicore processors in edge computingYanchun Liu0Hongxue Qu1Shuang Chen2Xuejun Feng3Department of Computer and Software Engineering, Shandong College of Electronic TechnologyDepartment of Computer and Software Engineering, Shandong College of Electronic TechnologyDepartment of Computer and Software Engineering, Shandong College of Electronic TechnologyInspur Communication Information Systems Co., Ltd.Abstract Edge computing faces challenges in energy-efficient task scheduling for heterogeneous multicore processors (HMPs). Existing solutions focus on reactive workload adaptation and energy prediction but fail to effectively integrate dynamic voltage and frequency scaling (DVFS). This paper proposes a novel algorithm integrating task prioritization, core-aware mapping, and predictive DVFS. Our approach outperforms state-of-the-art methods, reducing energy consumption by 20.9% while maintaining a low 2.4% deadline miss rate. Experiments on real HMP platforms demonstrate the algorithm’s scalability and adaptability to varying workloads. This work advances energy-efficient edge computing, balancing performance and power constraints.https://doi.org/10.1038/s41598-025-92604-6Edge computingHeterogeneous multicore processorsEnergy-efficient task schedulingDVFSTask mappingTask priority assignment |
| spellingShingle | Yanchun Liu Hongxue Qu Shuang Chen Xuejun Feng Energy efficient task scheduling for heterogeneous multicore processors in edge computing Scientific Reports Edge computing Heterogeneous multicore processors Energy-efficient task scheduling DVFS Task mapping Task priority assignment |
| title | Energy efficient task scheduling for heterogeneous multicore processors in edge computing |
| title_full | Energy efficient task scheduling for heterogeneous multicore processors in edge computing |
| title_fullStr | Energy efficient task scheduling for heterogeneous multicore processors in edge computing |
| title_full_unstemmed | Energy efficient task scheduling for heterogeneous multicore processors in edge computing |
| title_short | Energy efficient task scheduling for heterogeneous multicore processors in edge computing |
| title_sort | energy efficient task scheduling for heterogeneous multicore processors in edge computing |
| topic | Edge computing Heterogeneous multicore processors Energy-efficient task scheduling DVFS Task mapping Task priority assignment |
| url | https://doi.org/10.1038/s41598-025-92604-6 |
| work_keys_str_mv | AT yanchunliu energyefficienttaskschedulingforheterogeneousmulticoreprocessorsinedgecomputing AT hongxuequ energyefficienttaskschedulingforheterogeneousmulticoreprocessorsinedgecomputing AT shuangchen energyefficienttaskschedulingforheterogeneousmulticoreprocessorsinedgecomputing AT xuejunfeng energyefficienttaskschedulingforheterogeneousmulticoreprocessorsinedgecomputing |