1. 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
†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
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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
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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
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5. FTT and DREQUIEMI
integration (1/3)
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6. FTT and DREQUIEMI
integration (2/3)
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7. FTT and DREQUIEMI
integration (3/3)
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8. System overview
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9. Choreographies set
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10. T and S choreographies
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11. C and P choreographies
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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)
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13. Implementation issues:
Convergence Layer
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14. Example 1: real-time
producer consumer (1/2)
Every 10 ms Maximum Process data
generates a network delay: coming from a
sample 20 ms producer
10 10
producer consumer
slave slave
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15. Example real-time
producer consumer (2/2)
Every 10 ms Maximum network Process data
generates a sample delay: coming from a
20 ms producer
10 10
producer consumer
slave slave
PC# Produce# producer # CC.data
O= 5ms master
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
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16. Experiments (1/2)
Master-slave
templates
End-to-End costs (us) Convergence
Layer
over 796 MHz-100Mbps
DREQUIEMI
J2ME-RMIOP
JTime
TimesysOs
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17. Experiments (2/2) Master-slave
templates
End-to-End costs (bytes) Convergence
Layer
over 796 MHz-100Mbps
DREQUIEMI
J2ME-RMIOP
JTime
TimesysOs

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