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Scheduling Self-Suspending Tasks: New and Old Results

Authors Jian-Jia Chen , Tobias Hahn, Ruben Hoeksma , Nicole Megow , Georg von der Brüggen



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Author Details

Jian-Jia Chen
  • TU Dortmund University, Germany
Tobias Hahn
  • University of Bremen, Germany
Ruben Hoeksma
  • University of Bremen, Germany
Nicole Megow
  • University of Bremen, Germany
Georg von der Brüggen
  • TU Dortmund University, Germany

Acknowledgements

The authors thank Minming Li from City University of Hong Kong and Guillaume Sagnol from TU Berlin, for discussions in an early stage of this research. The authors also thank the organizing committee of MAPSP 2017 for planning a discussion session during the workshop, which initialized the study in this paper.

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Jian-Jia Chen, Tobias Hahn, Ruben Hoeksma, Nicole Megow, and Georg von der Brüggen. Scheduling Self-Suspending Tasks: New and Old Results. In 31st Euromicro Conference on Real-Time Systems (ECRTS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 133, pp. 16:1-16:23, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.ECRTS.2019.16

Abstract

In computing systems, a job may suspend itself (before it finishes its execution) when it has to wait for certain results from other (usually external) activities. For real-time systems, such self-suspension behavior has been shown to induce performance degradation. Hence, the researchers in the real-time systems community have devoted themselves to the design and analysis of scheduling algorithms that can alleviate the performance penalty due to self-suspension behavior. As self-suspension and delegation of parts of a job to non-bottleneck resources is pretty natural in many applications, researchers in the operations research (OR) community have also explored scheduling algorithms for systems with such suspension behavior, called the master-slave problem in the OR community. This paper first reviews the results for the master-slave problem in the OR literature and explains their impact on several long-standing problems for scheduling self-suspending real-time tasks. For frame-based periodic real-time tasks, in which the periods of all tasks are identical and all jobs related to one frame are released synchronously, we explore different approximation metrics with respect to resource augmentation factors under different scenarios for both uniprocessor and multiprocessor systems, and demonstrate that different approximation metrics can create different levels of difficulty for the approximation. Our experimental results show that such more carefully designed schedules can significantly outperform the state-of-the-art.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Real-time systems
Keywords
  • Self-suspension
  • master-slave problem
  • computational complexity
  • speedup factors

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