Control Strategy of Task Scheduling Permission in Cyber-physical System

doi:10.3969/j.issn.1000-3428.2017.04.010

Abstract

Abstract: The computer temporal constraint and the hardware energy consumption threshold may have a conflict,when the tasks of Cyber-physical System(CPS) are scheduled,and that cannot guarantee correct execution sequence.In order to solve this problem,a control strategy of task scheduling permissions is proposed.Super-dense time model is used to express global time signal.The remainder value density,execution enthusiasm and resource consumption of events are used to represent the quantity of value,deadline and energy consumption of tasks.Equipment and resources are distributed for real-time tasks,and the occurrence of thrashing are reduced.Simulation results show that this strategy can improve the cumulative value of tasks,and reduces the energy consumption and execution time,achieves higher overall efficiency of the system.

Key words: Cyber-physical System(CPS), scheduling permission, quantity of value, deadline, energy consumption

摘要： 信息物理系统任务调度中计算时序约束与硬件能耗阈值存在冲突,难以保证执行顺序正确。为此,提出一种任务调度权限控制策略。采用超致密时间模型表达全局时间信号,以事件的剩余价值密度、执行积极性、资源消耗3个约束条件刻画任务的价值量、截止期及能耗,为任务实时分配设备与资源,减少颠簸现象。仿真结果表明,该策略能提高任务累积价值,降低能耗与执行时间,使系统获取更高的综合效益。

关键词: 信息物理融合系统, 调度权限, 价值量, 截止期, 能耗

CLC Number:

TP302.7

ZHANG Jing,CHEN Yao,FAN Hongbo,SUN Jun. Control Strategy of Task Scheduling Permission in Cyber-physical System[J]. Computer Engineering.

张晶,陈垚,范洪博,孙俊. 信息物理融合系统任务调度权限控制策略[J]. 计算机工程.

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URL:

https://www.ecice06.com/EN/Y2017/V43/I4/60

References

参考文献［1］温景容,武穆清,宿景芳.信息物理融合系统［J］.计算机学报,2012,38(4):507-517. ［2］王中杰,谢璐璐.信息物理融合系统研究综述［J］.自动化学报,2011,37(10):1157-1166. ［3］何积丰.Cyber-physical Systems［J］.中国计算机学会通讯,2010,6(1):25-29. ［4］Edward A L.Cyber Physical Systems:Design Challenges［C］//Proceedings of International Symposium on Object/Component/Service-oriented Real-time Distributed Com-puting.Washington D.C.,USA:IEEE Press,2008:1-8. ［5］Akkaya I,Patricia D,Shuhei E,et al.Systems Engi-neering for Industrial Cyber-physical Systems Using Aspects［J］.Proceedings of the IEEE,2016,104(5):1-16. ［6］李仁发,谢勇,李蕊,等.信息-物理融合系统若干关键问题综述［J］.计算机研究与发展,2012,49(6):1149-1161. ［7］徐洪智,李仁发,曾理宁.基于Ptolemy的信息物理融合系统建模与仿真［J］.系统仿真学报,2014,26(8):1633-1638. ［8］徐洪智,李仁发,曾理宁.基于Ptolemy的自适应巡航系统建模与仿真［J］.计算机工程,2015,41(6):28-32. ［9］Zhao Yang,Xiong Yuhong,Edward A L,et al.The Design and Application of Structured Types in Ptolemy II［J］.International Journal of Intelligent System,2010,25(2):118-136. ［10］Alur R,Dill D L.A Theory of Timed Automata［J］.Theoretical Computer Science,1994,126(2):183-235. ［11］孙家泽,王曙燕,曹小鹏.用于测试用例最小化问题的改进PSO算法［J］.计算机工程,2009,35(15):201-202. ［12］Qian Zhilin,Yu Huiqun,Fan Guisheng.Modeling of Adaptive Cyber Physical Systems Using Aspect-oriented Approach［J］.Applied Mathematics and Information Sciences,2015,9(4):1981-1992. ［13］夏家莉,陈辉,杨兵.一种动态优先级实时任务调度算法［J］.计算机学报,2012,35(12):2685-2694. ［14］黄姝娟,朱怡安,李兵哲,等.具有依赖关系的周期任务实时调度方法［J］.计算机学报,2015,38(5):999-1006. ［15］王剑平,张云生,张果,等.嵌入式控制状状转移的确定性实时语义［J］.控制与决策,2014,29(1):83-88. 编辑刘冰

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