Dynamic power management based on subtask and executing time

被引：0
|
作者：
Jiang L. [1 ,2 ]
Yang G. [1 ]
Li H. [1 ]
机构：
[1] Shanghai Institute of Micro-system and Information Technology, Chinese Academy of Science
[2] Graduate School, Chinese Academy of Science
来源：
Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | 2010年 / 45卷 / 03期
关键词：
Break-even point; Dynamic power management; SEBDSP(subtask and executing time-based device-scheduling policy); Subtask executing time;
D O I：
10.3969/j.issn.0258-2724.2010.03.020
中图分类号：
学科分类号：
摘要：
In order to reduce the energy consumption of embedded systems, a subtask and executing time-based device scheduling policy (SEBDSP) was proposed by analyzing the drawbacks of EODSA (the energy-optimal device-scheduling algorithm) and IEODSA1 (the improved EODSA1). The SEBDSP divides tasks into several sub-tasks and manages I/O (input/output) devices in light of the executing time of the subtasks and the break-even points of the devices to extend the application area of the EODSA and the IEODSA1. The experimental results show that the average power consumption is respectively 31.94% and 4.95% lower with the proposed policy than with the EODSA and the IEODSA1.
引用
收藏
页码：435 / 439
页数：4
相关论文
共 15 条
  • [1] Jiang Q., Xi H., Yin B., The equivalent relation between timeout and stochastic policies for dynamic power management, Journal of Computer-Aided Design & Computer Graphics, 21, 11, pp. 1646-1651, (2009)
  • [2] Jiang Q., Xi H., Yin B., Stochastic switching model and policy optimization online for dynamic power management, Acta Automatica Sinica, 33, 1, pp. 66-72, (2007)
  • [3] Chu Y., Zhao M., Dynamic power management based on Markov process, Journal of University of Electronic Science and Technology of China, 36, 3, pp. 521-523, (2007)
  • [4] Liu F., Mai W., Huang K., Design and implementation of stochastic model algorithm for dynamic power management, Journal of South China University of Technology: Natural Science Edition, 35, 9, pp. 60-65, (2007)
  • [5] Chen J., Gao D., Zheng Q., A research on an optimized adaptive dynamic power management, Proc. of the 2nd IEEE International Conference on Computer Science and Information Technology, pp. 52-55, (2009)
  • [6] Chung E.Y., Benini L., Dynamic power management for non-stationary service requests, IEEE Trans. on Computers, 51, 11, pp. 1345-1361, (2002)
  • [7] Douglis F., Krishnan P., Bershad B., Adaptive disk spin-down policies for mobile computers, Proc. of the 2nd Usenix Symp. on Mobile and Location-Independent Computing (MOBLIC), pp. 121-137, (1995)
  • [8] Golda A., Kos A., Effective supervisors for predictive methods of dynamic power management, Proc. of the Mixed Design of Integrated Circuits and Systems, pp. 381-386, (2007)
  • [9] Helmbold D.P., Long D.D.E., Sherrod B., A dynamic disk spin-down technique for mobile computing, Proc. of the 2nd Annual ACM Int'l Conf. on Mobile Computing and Networking, pp. 130-142, (1996)
  • [10] Lu Y.H., De Micheli G., Adaptive hard disk power management on personal computers, Proc. of the 1999 IEEE Great Lakes Symposium on VLSI, pp. 50-53, (1999)
12