【摘要】 在实时嵌入式系统设计中,为了保证系统的安全运行,需要验证系统是否满足时限,即任务必须在截止期之前完成,否则实时系统将失败。目前衡量实时嵌入式系统实时性的重要指标是任务的最坏情况执行时间(Worst Case Execution Time,WCET)。文章首先综述了WCET分析以及研究WCET分析的主要方法。分析了在当前多核平台上、复杂处理器架构下WCET分析存在的主要问题,并根据当前WCET分析存在的问题展开讨论,分别针对时序分析、微系统结构分析和多核多任务调度策略等方面分析了国内外的研究进展。最后提出了一种基于深度学习的自适应实时DVFS算法,该算法可以进行动态电压和频率调节(DVFS),以达到节能的目的;同时还能够动态修正程序的WCET值,为未来嵌入式系统中的WCET分析与预测提供指导方法。更多还原

【Abstract】 For the safe operation of real-time embedded system,verifying whether the system meet the duration limitation is necessary.That means the task must be completed before the deadline,otherwise the real-time system will fail.At present,the worst-case execution time(WCET) is one of the important indicators to measure the real-time embedded system.This paper firstly introduces WCET analysis itself and main methods for this analysis.Secondly,the main problems of WCET analysis under complex processor architecture on current multi-core platforms are investigated.Thirdly,the research progress in WCET analysis is discussed for timing analysis,micro-system structure analysis and multi-core and multi-task scheduling strategy based on the current problems.Finally,adaptive real-time DVFS algorithm based on deep learning is proposed,which can perform dynamic voltage and frequency adjustment(DVFS),achieve the target for energy saving,and dynamically correct the WCET value of the program to provide guidance for the analysis and prediction of WCET in future embedded systems.更多还原