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A Comparison of Partitioning Strategies for Fixed Points-based Limited Preemptive Scheduling
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. (Industrial Software Engineering)ORCID iD: 0000-0002-3210-3819
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-8461-0230
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-4157-3537
(English)In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050Article in journal (Refereed) Epub ahead of print
Abstract [en]

The increasing industrial demand for handling complex functionalities has influenced the design of hardware architectures for time critical embedded systems, during the past decade. Multi-core systems facilitate the inclusion of many complex functionalities, while, at the same time, inducing cache related overheads, as well as adding partitioning complexity to the overall system schedulability. One of the efficient paradigms for controlling and reducing the cache related costs in real-time systems is Limited Preemptive Scheduling (LPS), with its particular instance Fixed Preemption Points Scheduling (LP-FPPS), that has been shown to outperform other alternatives as well as has been supported by and investigated in the automotive domain. With respect to the partitioning constraints, Partitioned Scheduling has been widely used to pre-runtime allocate tasks to specific cores, resulting in a predictable cache-related preemption delays estimations. In this paper we propose to integrate LP-FPPS and Partitioned Scheduling on fixed-priority multicore real-time systems in order to increase the overall system schedulability.We define a new joint approach for task partitioning and preemption point selection, that is based on the computation of the maximum blocking tolerance upon each allocation, thus being able to quantify the schedulability of the taskset on each processor. Furthermore, we investigate partitioning strategies based on different heuristics, i.e. First Fit Decreasing and Worst Fit Decreasing, and priority and density taskset orderings. The evaluation performed on randomly generated tasksets shows that in the general case, no single partitioning strategy fully dominates the others. However, the evaluation results reveal that certain partitioning strategies perform significantly better with respect to the overall schedulability for specific taskset characteristics. The results also reveal that the proposed partitioning strategies outperform Fully Preemptive and Non-Preemptive partitioned scheduling in terms of successful partitioning.

Keywords [en]
Real-Time Systems, Partitioned Scheduling, Limited Preemptive Scheduling, Fixed Preemption Points
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:mdh:diva-39827DOI: 10.1109/TII.2018.2848879OAI: oai:DiVA.org:mdh-39827DiVA, id: diva2:1218581
Available from: 2018-06-14 Created: 2018-06-14 Last updated: 2018-06-26Bibliographically approved
In thesis
1. Improving the Schedulability of Real Time Systems under Fixed Preemption Point Scheduling
Open this publication in new window or tab >>Improving the Schedulability of Real Time Systems under Fixed Preemption Point Scheduling
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

During the past decades of research in Real-Time systems, non-preemptive scheduling and fully preemptive scheduling have been extensively investigated, as well as compared with each other. However, it has been shown that none of the two scheduling paradigms dominates over the other in terms of schedulability. In this context, Limited Preemptive Scheduling (LPS) has emerged as an attractive alternative with respect to, e.g., increasing the overall system schedu- lability, efficiently reducing the blocking by lower priority tasks (compared to non-preemptive scheduling) as well as efficiently controlling the number of preemptions, thus controlling the overall preemption-related delay (compared to fully-preemptive scheduling).

Several approaches within LPS enable the above mentioned advantages. In our work, we consider the Fixed Preemption Point Scheduling (LP-FPP) as it has been proved to effectively reduce the preemption-related delay compared to other LPS approaches. In particular, LP-FPP facilitates more precise estimation of the preemption-related delays, since the preemption points of a task in LP-FPP are explicitly selected during the design phase, unlike the other LPS approaches where the preemption points are determined at runtime.

The main goal of the proposed work is to improve the schedulability of real-time systems under the LP-FPP approach. We investigate its use in different domains, such as: single core hard real-time systems, partitioned multi-core systems and real-time systems which can occasionally tolerate deadline misses. We enrich the state of the art for the single core hard real-time systems by proposing a novel cache-related preemption delay analysis, towards reducing the pessimism of the previously proposed methods. In the context of partitioned multi-core scheduling we propose a novel partitioning criterion for the Worst-Fit Decreasing based partitioning, and we also contribute with the comparison of existing partitioning strategies for LP-FPP scheduling. Finally, in the context of real-time systems which can occasionally tolerate deadline misses, we contribute with a probabilistic response time analysis for LP-FPP scheduling and a preemption point selection method for reducing the deadline-misses of the tasks.

Place, publisher, year, edition, pages
Stockholm: E-Print AB, 2018. p. 180
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 270
Keywords
Real-Time Systems, Limited Preemptive Scheduling, Fixed Preemption Points Scheduling, Probabilistic response time analysis, Cache-Related Preemption Delay Analysis
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-39828 (URN)978-91-7485-390-2 (ISBN)
Presentation
2018-09-21, Kappa, Mälardalen University, Västerås, 13:15 (English)
Opponent
Supervisors
Available from: 2018-06-15 Created: 2018-06-14 Last updated: 2018-06-15Bibliographically approved

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