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A synchronous scheduling service (SSS) for distributed real-time Java

A synchronous scheduling service (SSS) for distributed real-time Java. Pablo Basanta -Val , Iria Estévez -Ayres, Marisol García-Valls , and Luis Almeida mailto:pbasanta@it.uc3m.es.

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A synchronous scheduling service (SSS) for distributed real-time Java

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  1. A synchronous scheduling service (SSS)for distributed real-time Java Pablo Basanta-Val, IriaEstévez-Ayres, Marisol García-Valls, and Luis Almeida mailto:pbasanta@it.uc3m.es †Jornadas de Tiempo Real 2011- Madrid( )Publicado en IEEE Transactions on Parallel and Distributed Systems

  2. Outline • Context and Motivation • FTT and DREQUIEMI integration • SSS (Synchronous Scheduling Service) • Master Slave Model • Choreographies • Choreographies scheduling/scheduler • Architecture and examples • Performance • Conclusion and ongoing work

  3. Context • Java programmers may use two specifications for develop their real-time applications • RTSJ: The Real-Time Specification for Java • DRTSJ: The Distributed Real-Time Specification for Java • DRTSJ has focused on remote object upcalling and abstractions (distributable threads). • But not in a predictable networks • Networks predictability is a requirement JRT-11

  4. In this work • We introduce time-triggered orientation in distributed real-time Java • Basic model used the FTT (Flexible Time-Triggered) protocol • Supported as a new service in distributed real-time Java • SSS (Synchronous Scheduling Service) • We obtain a more predictable network management • Useful for instance in high-integrity applications JRT-11

  5. FTT and DREQUIEMI integration (1/3) JRT-11

  6. FTT and DREQUIEMI integration (2/3) JRT-11

  7. FTT and DREQUIEMI integration (3/3) JRT-11

  8. System overview JRT-11

  9. Choreographies set JRT-11

  10. T and S choreographies JRT-11

  11. C and P choreographies JRT-11

  12. Scheduling Choreographies • Each choreography is modeled as non preemptive task • {O, T, C, D} • The choreographies executed by the master • It runs a NPR-EDF • Simple admission control (T=D) JRT-11

  13. Implementation issues: Convergence Layer JRT-11

  14. Every 10 ms generates a sample Maximum network delay: 20 ms Process data coming from a producer 10 10 producer slave consumer slave Example 1: real-time producer consumer (1/2) JRT-11

  15. Example real-time producer consumer (2/2) Every 10 ms generates a sample Maximum network delay: 20 ms Process data coming from a producer 10 10 consumer slave producer slave master • PC# Produce# producer # CC.dataO= 5ms • T= 10 ms • C= 2 ms • D= 10 ms NPR-EDF • CC # Consume# consumer# • O= 15 ms • T= 10 ms • C= 2 ms • D= 10 ms JRT-11

  16. Master-slave templates Convergence Layer DREQUIEMI J2ME-RMIOP JTime TimesysOs Experiments (1/2)End-to-End costs (us) over 796 MHz-100Mbps JRT-11

  17. Master-slave templates Convergence Layer DREQUIEMI J2ME-RMIOP JTime TimesysOs Experiments (2/2) End-to-End costs (bytes) over 796 MHz-100Mbps JRT-11

  18. Master-slave templates Convergence Layer DREQUIEMI J2ME-RMIOP JTime TimesysOs Jitter [new]time vs. event triggered JRT-11

  19. Conclusions • Developed techniques to include time-triggered orientation in distributed real-time Java • Synchronous Scheduling Service (SSS) • Empirical evidences showed better performance than an ET approach • Because TCP/IP stacks and OS are not fully preemptive JRT-11

  20. Ongoing work • Developing a minimum time-triggered implementation without DREQUIEMI • Ongoing master thesis • Changes in the model • NPR-RMS model vs. NPR-EDF • One way choreographies JRT-11

  21. JRT-11

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