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通信竞争的混合关键级系统多DAG动态调度策略 被引量:3

Multiple DAGs Dynamic Scheduling for Mixed-Criticality Systems with Communication Contention
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摘要 以多DAG模型研究通信竞争的混合关键级系统(mixed-criticality systems)的调度问题是适应现代汽车电子系统异构化和分布式的需要.首先实现通信竞争环境下"向上排序值(upward rank value)"和"最早完成时间(earliest finish time)"中时间的精确分析,以适应系统中计算与网络均异构,且任务与消息的同步特征.接着提出公平策略的多DAG动态任务与消息调度F_MDDTMS算法,以降低系统的调度长度;提出关键级策略的多DAG动态任务与消息调度C_MDDTMS算法,以确保高关键级应用的实时性;结合F_MDDTMS算法和C_MDDTMS算法,提出混合关键级策略的多DAG动态任务与消息调度MC_MDDTMS算法,既确保混合关键级系统中高关键级应用的实时性,又使得低关键级应用得到积极的处理.实例分析和实验结果验证了提出的算法在调度长度、不公平性、最差响应时间和实时性上的优越性. The scheduling of mixed-criticality systems with communication contention based on multiple DAGs model is the requirement of automobile electronic systems with heterogeneity and distribution.Firstly,the more accurate "upward rank value"and "earliest finish time"with communication contention on time are implemented to adapt to the heterogeneity of both computing and networking,and the synchronization of task and message in this paper.Then,an algorithm called fairness on multiple DAGs dynamic task and message scheduling(F_MDDTMS)is proposed to reduce scheduling length.An algorithm called criticality on multiple DAGs dynamic task and message scheduling(C_MDDTMS)is proposed to ensure the real-time of higher criticality applications.An algorithm called mixed criticality on multiple DAGs dynamic task and message scheduling(MC_MDDTMS)is also proposed based on the joint of F_MDDTMS algorithm and C_MDDTMS algorithm to ensure hard real-time of higher criticality applications and the activity of lower criticality applications of mixed-criticality systems.Example analysis and experimental results show that the proposed algorithms are excellent on scheduling length,unfairness, worst-case response time(WCRT)and real-time.
出处 《计算机研究与发展》 EI CSCD 北大核心 2015年第11期2608-2621,共14页 Journal of Computer Research and Development
基金 国家自然科学基金项目(61173036 61202102 61300039 61300037 61502405) 国家"八六三"高技术研究发展计划基金项目(2012AA01A301-01)
关键词 通信竞争 混合关键级系统 多DAG 动态调度 实时性 communication contention mixed-criticality systems multiple DAGs dynamic scheduling real-time
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参考文献28

  • 1Xie Guoqi, Li Renfa, Xiao Xiongren, et al. A high- performance DAG task scheduling algorithm for heterogeneous networked embeddel systems [C] //Proc of the 28th IEEE Int Conf on Advanced Information Networking and Applications. Piscataway, NJ: IEEE, 2014:1011-1016.
  • 2谢国琪,李仁发,杨帆,黄卫红.异构网络化汽车电子系统中多DAG离线任务调度[J].通信学报,2013,34(12):20-32. 被引量:4
  • 3Di N M. Design and development of component-based embedded systems for automotive applications [C] //Proc of the 13th Aria-Europe Int Conf on Reliable Software Technologies. Berlin.. Springer, 2008 15-29.
  • 4Vestal S. Preemptive scheduling of multi-criticality systems with varying degrees of execution time assurance [C] /[Proe of the 28th IEEE Real-Time Systems Symp. Piscataway, NJ: IEEE, 2007:239-243.
  • 5Sinha P. Architectural design and reliability analysis of a fail- operational brake-by-wire system from ISO 26262 perspectives [J]. Reliability Engineering gx System Safety, 2011, 96(10): 1349-1359.
  • 6Zeller M, Prehofer C, Weiss G, et al. Towards self- adaptation in real-time, networked systems: Efficient solving of system constraints for automotive embedded systems [C] /[Proc of the 5th IEEE Int Conf on Self-Adaptive and Self-Organizing Systems. Piscataway, NJ: IEEE, 2011: 9- 88.
  • 7Katoen J P, Noll T, Wu H, et al. Model-based energy optimization of automotive control systems [C] [/Proc of the Conf on Design, Automation and Test in Europe. Piscataway, NJ IEEE, 2013 : 761-766.
  • 8Heinrich P, Prehofer C. Network-wide energy optimization for adaptive embedded systems [J]. ACM SIGBED Review, 2013, 10(1): 33-36.
  • 9Topcuoglu H, Hariri S, Wu M. Performance-effective and low-complexity task scheduling for heterogeneous computing [J]. IEEE Trans on Parallel and Distributed Systems, 2002, 13(3), 260-274.
  • 10Khan M A. Scheduling for heterogeneous systems using constrained critical paths [J]. Parallel Computing, 2012, 38 (4): 175-193.

二级参考文献46

  • 1ALBERT A. Comparison of event-triggered and time-triggered concepts with regard to distributed control systems[A]. Proceedings of Embedded World[C]. Gelsenkirchen, Germany, 2004. 235-252.
  • 2NAVET N, SONG Y , SIMONOT-LION F, et al. Trends in automotive communication systems[J]. IEEE, 2005, 93(6): 1204-1224.
  • 3FlexRay consortium, FlexRay communication systems-protocol speci- fication, version 3.0 [EB/OL]. http://www.flexray.com, 2009.
  • 4HU X, XING G, LEUNG J. Exploring the interplay between computa- tion and communication in distributed real-time scheduling[J]. IEEE Transactions on Computer, 2011, 60(12):1759-1771.
  • 5TRAIAN P, PAUL P, PETRU E, et al. Timing analysis of the FlexRay communication protocol[A]. Proceedings of Euro-micro Conference on Real-Time Systems[C]. Dresden, Germany, 2006. 203-216.
  • 6TRAIAN P, PAUL P, PETRU E, et al. Bus access optimization for FlexRay-based distributed embedded systems[A]. Proceedings of the Design, Automation and Test in European Conference[C]. Nice, France. 2007.51-56.
  • 7INSEOK P, MYOUNGHO S. FlexRay network parameter optimiza- tion method for automotive applications[J]. IEEE Transactions on In- dustrial Electronics, 2011, 58(4): 1449-1459.
  • 8GRENIER M, HAVET L, NAVET N. Configuring the on FlexRay: the case of the static segment[A]. Proceedings of the ERTS[C]. Toulouse, France, 2008.
  • 9SOHEIL S, YIN Y F, PENG Z B, et al. Immune genetic algorithms for optimization of task priorities and FlexRay frame identifiers[A]. Pro- ceedings of IEEE International Conference on Embedded and Real-Time Computing Systems and Applications[C]. Beijing, China, 2009. 486-493.
  • 10MARTIN L, MICHAEL G, JURGEN T, et al. FlexRay schedule optimization of the static segment[A]. Proceedings of the 7th IEEE/ ACM International Conference on Co-design and System Synthesis[C]. Grenoble, France, 2009. 363-372.

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