Abstract
Work stealing has proven to be an efficient technique for scheduling parallel computations. In its basic form, however, work stealing is not suitable for real-time applications, since the latency of a task is hardly predictable. In this paper, we propose a number of variants and extensions of work stealing suitable for stream processing applications. Such applications are frequently encountered in embedded systems, which often have to obey real-time constraints. Moreover, we give bounds on the maximum latency for certain stealing strategies. Our experimental results show a significant reduction of the latency using these strategies.
This work was partially funded by the German Federal Ministry of Education and Research (BMBF) as part of the alliance project SPES2020, grant 01IS08045.
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Mattheis, S., Schuele, T., Raabe, A., Henties, T., Gleim, U. (2012). Work Stealing Strategies for Parallel Stream Processing in Soft Real-Time Systems. In: Herkersdorf, A., Römer, K., Brinkschulte, U. (eds) Architecture of Computing Systems – ARCS 2012. ARCS 2012. Lecture Notes in Computer Science, vol 7179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28293-5_15
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