计算机应用 ›› 2015, Vol. 35 ›› Issue (12): 3515-3519.DOI: 10.11772/j.issn.1001-9081.2015.12.3515

• 计算机软件技术 • 上一篇    下一篇

面向可信嵌入式系统的随机实时任务能耗优化

潘雄, 江维, 文亮, 周可染, 董琪, 王峻龙   

  1. 电子科技大学信息与软件工程学院, 成都 610054
  • 收稿日期:2015-06-10 修回日期:2015-07-16 出版日期:2015-12-10 发布日期:2015-12-10
  • 通讯作者: 潘雄(1989-),男,湖北孝感人,硕士研究生,主要研究方向:可信嵌入式系统能耗优化、嵌入式系统安全
  • 作者简介:江维(1981-),男,四川乐山人,副教授,博士,主要研究方向:可信计算、分布式实时系统、无线网络;文亮(1990-),男,四川绵阳人,硕士研究生,主要研究方向:嵌入式安全、嵌入式系统设计;周可染(1991-),男,辽宁沈阳人,硕士研究生,主要研究方向:软件工程、信息管理系统、嵌入式系统设计;董琪(1992-),男,山东临沂人,硕士研究生,主要研究方向:混合关键系统、嵌入式系统设计;王峻龙(1993-),男,四川乐山人,硕士研究生,主要研究方向:可信计算、分布式计算、嵌入式系统设计。
  • 基金资助:
    核高基重大专项(2012ZX01033001-001);国家自然科学基金资助项目(61300092,61003032);中央高校基本科研业务费专项资金资助项目(ZYGX2013J068)。

Energy consumption optimization of stochastic real-time tasks for dependable embedded system

PAN Xiong, JIANG Wei, WEN Liang, ZHOU Keran, DONG Qi, WANG Junlong   

  1. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 610054, China
  • Received:2015-06-10 Revised:2015-07-16 Online:2015-12-10 Published:2015-12-10

摘要: 针对可信嵌入式系统应用中将任务的最坏情况下的执行时间(WCET)作为任务的实际执行时间,导致系统资源的极大浪费的问题,提出了一种基于随机任务概率模型的方法。首先,考虑任务执行时间具有特定概率分布,并且任务具有不错过其死限的概率(NDVP)需求,同时考虑了动态电压和频率调整(DVFS)对系统可靠性的影响,利用该技术降低能耗。然后,基于动态规划算法,提出了一种具有多项式运行时间的优化算法,并进一步设计了状态剔除规则降低算法运行开销。仿真表明,所提算法与最坏执行时间模型下的最优算法相比,系统能耗降低了30%以上。实验结果表明,考虑任务的随机执行时间能在保证系统可靠性的同时大大节约系统资源。

关键词: 能耗, 随机任务, 动态电压和频率调整, 可靠性, 动态规划

Abstract: The WCET (Worst Case Execution Time) is taken as the actual execution time of the task, which may cause a great waste of system resource. In order to solve the problem, a method based on stochastic task probability model was proposed. Firstly, Dynamic Voltage and Frequency Scaling (DVFS) was utilized to reduce the energy consumption by considering the effect of DVFS on the reliability of the system, the specific probability distribution of task execution time and the task requirement of No-Deadline Violation Probability (NDVP). Then, a new optimization algorithm with the operation time of polynomial was proposed based on the dynamic programming algorithm. In addition, the execution overhead of the algorithm was reduced by designing the state eliminating rules. The simulation results show that, compared with the optimal algorithm of the model of WCET, the proposed algorithm can reduce the system energy consumption by more than 30%. The experimental results indicate that considering the random execution time of tasks can save the system resources while ensuring the reliability of the system.

Key words: energy consumption, stochastic task, Dynamic Voltage and Frequency Scaling (DVFS), reliability, dynamic programming

中图分类号: