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Feedback-based admission control for hard real-time task allocation under dynamic workload on many-core systems

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Title of host publicationArchitecture of Computing Systems -- ARCS 2016
DatePublished - 26 Mar 2016
Pages157-169
Number of pages13
PublisherSpringer-Verlag
Original languageEnglish
ISBN (Electronic)978-3-319-30695-7
ISBN (Print)9783319306940

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9637
ISSN (Print)03029743
ISSN (Electronic)16113349

Abstract

In hard real-time systems, a computationally expensive schedulability analysis has to be performed for every task. Fulfilling this requirement is particularly tough when system workload and service capacity are not available a priori and thus the analysis has to be conducted at runtime. This paper presents an approach for applying controltheory-based admission control to predict the task schedulability so that the exact schedulability analysis is performed only to the tasks with positive prediction results. In case of a careful fine-tuning of parameters, the proposed approach can be successfully applied even to many-core embedded systems with hard real-time constraints and other time-critical systems. The provided experimental results demonstrate that, on average, only 62% of the schedulability tests have to be performed in comparison with the traditional, open-loop approach. The proposed approach is particularly beneficial for heavier workloads, where the number of executed tasks is almost unchanged in comparison with the traditional open-loop approach. By our approach, only 32% of exact schedulability tests have to be conducted. Moreover, for the analysed industrial workloads with dependent jobs, the proposed technique admitted and executed 11% more tasks while not violating any timing constraints.

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