ZHANG Longxin, TONG Zhao, ZHU Ningbo, XIAO Zheng, LI Kenli. Energy-Aware Scheduling with Uncertain Execution Time for Real-Time Systems[J]. Chinese Journal of Electronics, 2017, 26(1): 42-49. doi: 10.1049/cje.2016.10.011
Citation: ZHANG Longxin, TONG Zhao, ZHU Ningbo, XIAO Zheng, LI Kenli. Energy-Aware Scheduling with Uncertain Execution Time for Real-Time Systems[J]. Chinese Journal of Electronics, 2017, 26(1): 42-49. doi: 10.1049/cje.2016.10.011

Energy-Aware Scheduling with Uncertain Execution Time for Real-Time Systems

doi: 10.1049/cje.2016.10.011
Funds:  This work is supported by the Key Program of National Natural Science Foundation of China (No.61133005, No.61432005), the National Natural Science Foundation of China (No.61370095, No.61472124, No.61402157, No.61572175, No.61502165, No.61572177), and the Research Foundation of Education Bureau of Hunan Province (No.15C0400).
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  • Corresponding author: TONG Zhao (corresponding author) was born in 1985, received the Ph.D. degree in computer science from Hunan University, China, in 2014. His research interest includes modeling and scheduling for parallel and distributed computing systems, parallel system reliability, and parallel algorithms. (Email:tongzhao1985@yahoo.com.cn)
  • Received Date: 2014-01-10
  • Rev Recd Date: 2015-03-10
  • Publish Date: 2017-01-10
  • Energy-saving is extraordinary important for real-time systems. Dynamic voltage scaling (DVS) is an important technique to reduce the energy consumption of processors that support voltage scaling. It has been exploited extensively in task scheduling. However, many approaches take simple treatments and some of them even neglect the large voltage transition overheads. Although some strategies consider the penalty, frequency switching produces extra large time overhead and deadline misses occur frequently. In our paper, we propose an energy efficient soft real-time dynamic program scheme by using quantitative switching overhead and communication penalty for multitask scheduling with uncertain execution time. The experiments show that our approaches significantly outperform existing solutions both on simple-core and multi-core systems in terms of energy-saving.
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