Elastic Scheduling for Parallel Real-Time Systems

Authors James Orr , Chris Gill , Kunal Agrawal , Jing Li , Sanjoy Baruah

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Author Details

James Orr
  • {Washington University in St. Louis, 1 Brookings Dr, St. Louis, MO 63130, USA
Chris Gill
  • Washington University in St. Louis, 1 Brookings Dr, St. Louis, MO 63130, USA
Kunal Agrawal
  • Washington University in St. Louis, 1 Brookings Dr, St. Louis, MO 63130, USA
Jing Li
  • New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA
Sanjoy Baruah
  • Washington University in St. Louis, 1 Brookings Dr, St. Louis, MO 63130, USA

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James Orr, Chris Gill, Kunal Agrawal, Jing Li, and Sanjoy Baruah. Elastic Scheduling for Parallel Real-Time Systems. In LITES, Volume 6, Issue 1 (2019). Leibniz Transactions on Embedded Systems, Volume 6, Issue 1, pp. 05:1-05:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


The elastic task model was introduced by Buttazzo et al.~in order to represent recurrent real-time workloads executing upon uniprocessor platforms that are somewhat flexible with regards to timing constraints.  In this work, we propose an extension of this model and apply it to represent recurrent real-time workloads that exhibit internal parallelism and are executed on multiprocessor platforms. In our proposed extension, the elasticity coefficient - the quantitative measure of a task's elasticity that was introduced in the model proposed by Buttazzo et al. - is interpreted in the same manner as in the original (sequential) model. Hence, system developers who are familiar with the elastic task model in the uniprocessor context may use our more general model as they had previously done, now for real-time tasks whose computational demands require them to utilize more than one processor.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Real-time schedulability
  • Computer systems organization → Real-time system architecture
  • Computer systems organization → Real-time system specification
  • Computer systems organization → Embedded software
  • Parallel real-time tasks
  • multiprocessor federated scheduling
  • elasticity coefficient


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