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Scheduling of Datacompression on Distributed Systems with Time- and Event-Triggered Messages

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Architecture of Computing Systems - ARCS 2017 (ARCS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10172))

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Abstract

The compression of messages can improve schedulability by decreasing network latencies and contention at the cost of computational overhead for compression and decompression. Existing scheduling models do not consider compression as required for the deployment in distributed real-time systems. This paper presents an MILP model with decision variables, constraints and an objective function for selectively compressing messages as required for minimizing the system’s makespan, thereby optimizing the trade-off between communication time and computational overhead. We consider multi-hop communication in systems with multiple routers and computational nodes. The algorithm is evaluated using example scenarios and the results are compared to previous work without compression support.

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Notes

  1. 1.

    http://www.uni-siegen.de/cluster/hardware.html.

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Acknowledgements

This work has been supported by the DFG project DAKODIS under the Grant Agreement No. 275601549 and the European project DREAMS under the Grant Agreement No. 610640.

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Authors and Affiliations

  1. Embedded Systems Group, University of Siegen, Siegen, Germany

    Damian Ludwig & Roman Obermaisser

Authors
  1. Damian Ludwig
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  2. Roman Obermaisser
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Corresponding author

Correspondence to Damian Ludwig .

Editor information

Editors and Affiliations

  1. Vienna University of Technology, Vienna, Austria

    Jens Knoop

  2. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Wolfgang Karl

  3. Lawrence Livermore National Laboratory, Livermore, USA

    Martin Schulz

  4. Kyushu University, Fukuoka, Japan

    Koji Inoue

  5. Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany

    Thilo Pionteck

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Ludwig, D., Obermaisser, R. (2017). Scheduling of Datacompression on Distributed Systems with Time- and Event-Triggered Messages. In: Knoop, J., Karl, W., Schulz, M., Inoue, K., Pionteck, T. (eds) Architecture of Computing Systems - ARCS 2017. ARCS 2017. Lecture Notes in Computer Science(), vol 10172. Springer, Cham. https://doi.org/10.1007/978-3-319-54999-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-54999-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54998-9

  • Online ISBN: 978-3-319-54999-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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