International Journal of Automotive Technology

, Volume 20, Issue 5, pp 873–883 | Cite as

Scalable Holistic Scheduling of Safety-critical Systems on In-vehicle TDMA Networks

  • Darbandi Armaghan
  • Myung Kyun KimEmail author


Recently, the authors have proposed a scalable holistic scheduling approach for time-triggered applications on FlexRay, under end-to-end deadline and data dependency constraints. This approach divides the problem to two sub-problems that can be solved separately. The first sub-problem optimally schedules the set of messages to minimize number of used slots, and with respect to information exchanges between tasks and messages, end-to-end deadlines and FlexRay protocol constraints. The second sub-problem optimally schedules the set of tasks to minimize tasks response times, with respect to the solution returned by the first sub-problem. In this paper, our goal is to increase the scalability of our solution to each sub-problem. We propose a greedy heuristic approach for the first sub-problem that can find feasible solutions at a low runtime cost. In addition, to resolve assignment conflicts, we apply rescheduling the conflicted application with offset modification and priority promotion procedures. Furthermore, we show that the task scheduling in the second sub-problem can be divided into K independent child sub-problems, where K is the number of ECUs. Our experiments show high scalability and efficiency of our approaches comparing with our optimization-based approaches in the previous work.

Key words

FlexRay Distributed embedded systems Holistic scheduling Precedence constraints 



length of FlexRay cycle


number of communication cycles in a FlexRay cycle


number of ECUs


length of static slot


number of static slots in static segment


length of communication cycle


set of ECUs

G = (V, E)

DAG of application g


set of tasks


set of all messages communicating between tasks


set of messages communicating on the bus


period of application g


priority of application g


i-th task in application g


ECU that hosts τi


period of invocations of τi


execution time of τi


relative deadline of τi


offset of τi


worst case response time of τi


generated message by τi


repetition rate of mi


size of message mi in bits


k-th job of the task τi


generated message by τi,k


arrival time of task instance τi,k


start time of task instance τi,k


finish time of task instance τi,k


absolute deadline of task instance τi,k


instance graph of application g


end-to-end deadline of Path(τk,l,τp,q)


end-to-end delay of Path(τk,l,τp,q)


reduced DAG of Instance-Graph(g)


set of jobs in the path between mi,p and mj,q


time window assigned to jobs in Vi,pj,q


length of time window twi,pj,q


lower bound for transmission of mi,p


upper bound for transmission of mi,p


set of successor messages of mi,p in Reduced-Graph(g)


set of immediate successors of mi,p in Reduced-Graph(g)


set of immediate predecessors of mi,p in Reduced-Graph(g)


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This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (KNRF-2017030208).


  1. Abdelzaher, T. F. and Shin, K. G. (1999). Combined task and message scheduling in distributed real-time systems. Ieee Trans. Parallel And Distributed Systems 10, 11, 1179–1191.CrossRefGoogle Scholar
  2. Armaghan, D., Yoon, S. H. and Kim, M. K. (2017). Schedule construction under precedence constraints in FlexRay in-vehicle networks. Int. J. Automotive Technology 18, 4, 671–683.CrossRefGoogle Scholar
  3. Berwanger, J., Peller, M. and Griegbach, R. (1999). Byteflight — A new protocol for safety critical applications. FISITA World Automotive Cong., Seoul, Korea.Google Scholar
  4. Ding, S., Murakami, N., Tomiyama, H. and Takada, H. (2005). A GA-based scheduling method for FlexRay systems. Proc. 5th ACM Int. Conf. Embedded Software, Jersey City, New Jersey, USA.Google Scholar
  5. eCos (2002). Embedded Configurable Operating System. Google Scholar
  6. FlexRay Consortium (2010). The FlexRay Communication System Protocol Specification. Ver. 3.0.1.Google Scholar
  7. Fuehrer, T., Mueller, B., Hartwich, F. and Hugel, R. (2001). Time Triggered CAN (TTCAN). SAE Paper No. 2001-01-0073.Google Scholar
  8. Grenier, M., Havet, L. and Navet, N. (2008). Configuring the communication on FlexRay: The case of the static segment. Proc. 4th European Cong. Embedded Real Time Software, Toulouse, FranceGoogle Scholar
  9. Hu, M., Luo, J., Wang, Y., Lukasiewycz, M. and Zeng, Z. (2014). Holistic scheduling of real-time applications in time-triggered in-vehicle networks. IEEE Trans. Industrial Informatics 10, 3, 1817–1828.CrossRefGoogle Scholar
  10. IBM ILOG CPLEX (2011). Ver. 12.2.
  11. Kang, M., Park, K. and Jeong, M.-K. (2013). Framepacking for minimizing the bandwidth consumption of the FlexRay static segment. IEEE Trans. Industrial Electronics 60, 9, 4001–4008.CrossRefGoogle Scholar
  12. Kopetz, H. and Bauer, G. (2003). The time-triggered architecture. Proc. IEEE 91, 1, 112–126.CrossRefGoogle Scholar
  13. Kwok, Y. and Ahmad, I. (1996). Dynamic critical-path scheduling: An effective technique for allocating task graphs to multiprocessors. IEEE Trans. Parallel and Distributed Systems 7, 5, 506–521.CrossRefGoogle Scholar
  14. Lukasiewycz, M., Glas, M., Teich, J. and Milbredt, P. (2009). FlexRay schedule optimization of the static segment. Proc. 7th IEEE/ACM Int. Conf. Hardware/Software Codesign and System Synthesis, Grenoble, France.Google Scholar
  15. Lukasiewycz, M., Schneider, R., Goswami, D. and Chakraborty, S. (2012). Modular scheduling of distributed heterogeneous time-triggered automotive systems. Proc. 17th Asia and South Pacific Design Automation Conf., Sydney, Australia.Google Scholar
  16. Navet, N., Song, Y., Simonot-Lion, F. and Wilwert, C. (2005). Trends in automotive communication systems. Proc. IEEE 93, 6, 1204–1223.CrossRefGoogle Scholar
  17. OSEK/VDX Operating System Specification (2005). Ver. 2.2.3.
  18. Peng, D., Shin, K. G. and Abdelzaher, T. F. (1997). Assignment and scheduling communicating periodic tasks in distributed real-time systems. IEEE Trans. Software Engineering 23, 12, 745–758.CrossRefGoogle Scholar
  19. Pop, P., Poulsen, K. H., Izosimov, V. and Eles, P. (2007). Scheduling and voltage scaling for energy/reliability trade-offs in fault-tolerant time-triggered embedded systems. Proc. 5th IEEE/ACM/IFIP Int. Conf. Hardware/Software Codesign and System Synthesis (CODES+ISSS), Salzburg, Austria.Google Scholar
  20. Schenkelaars, T., Vermeulen, B. and Goossens, K. (2011). Optimal scheduling of switched FlexRay networks. Proc. Design, Automation & Test in Europe, Grenoble, France.Google Scholar
  21. Schmidt, K. and Schmidt, E. G. (2009). Message scheduling for the FlexRay protocol: The static segment. IEEE Trans. Vehicular Technology 58, 5, 2170–2179.CrossRefGoogle Scholar
  22. Tanasa, B., Bordoloi, U. D., Eles, P. and Peng, Z. (2010). Scheduling for fault-tolerant communication on the static segment of FlexRay. Proc. 31st IEEE Real-Time Systems Symp., San Diego, California, USA.Google Scholar
  23. The Autosar Consortium (2010). Autosar Flexray Interface Driver Specification. Ver. 4.0. Google Scholar
  24. Xiuqiang, H., Mingxuan, Y. and Zonghua, G. (2008). A hierarchical framework for design space exploration and optimization of TTP-based distributed embedded systems. IEEE Trans. Industrial Informatics 4, 4, 237–249.CrossRefGoogle Scholar
  25. Youn, J., Park, I. and Sunwoo, M. (2013). Heuristic resource allocation and scheduling method for distributed automotive control systems. Int. J. Automotive Technology 14, 4, 611–624.CrossRefGoogle Scholar
  26. Zeng, H., Natale, M., Ghosal, A. and Sangiovanni-Vincentelli, A. (2011). Schedule optimization of time-triggered systems communicating over the FlexRay static segment. IEEE Trans. Industrial Informatics 7, 1, 1–17.CrossRefGoogle Scholar

Copyright information

© KSAE 2019

Authors and Affiliations

  1. 1.School of Computer and Electrical EngineeringUniversity of UlsanUlsanKorea

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