a synchronous scheduling service 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

†Jornadas de Tiempo Real 2011- Madrid( ) Publicado en IEEE Transactions on Parallel and Distributed Systems

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

2

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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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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FTT and DREQUIEMI integration (1/3)

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FTT and DREQUIEMI integration (2/3)

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FTT and DREQUIEMI integration (3/3)

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System overview

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Choreographies set

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T and S choreographies

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C and P choreographies

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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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Implementation issues: Convergence Layer

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Example 1: real-time producer consumer (1/2)

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producerslave

consumerslave

Every 10 ms generates a sample

Process data coming from a producer

10 10

Maximum network delay: 20 ms

Example real-time producer consumer (2/2)

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PC# Produce# producer # CC.dataO= 5msT= 10 msC= 2 msD= 10 ms

CC # Consume# consumer# O= 15 msT= 10 msC= 2 msD= 10 ms

producerslave

consumerslave

Every 10 ms generates a sample

Process data coming from a producer

10 10

Maximum network delay: 20 ms

master

NPR-EDF

Experiments (1/2)End-to-End costs (us) over 796 MHz-100Mbps

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JTime

J2ME-RMIOP

TimesysOs

DREQUIEMI

Convergence Layer

Master-slave templates

Experiments (2/2) End-to-End costs (bytes) over 796 MHz-100Mbps

JTime

J2ME-RMIOP

TimesysOs

DREQUIEMI

Convergence Layer

Master-slave templates

Jitter [new]time vs. event triggered

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JTime

J2ME-RMIOP

TimesysOs

DREQUIEMI

Convergence Layer

Master-slave templates

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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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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