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Scheduling Elastic Applications in Compositional Real-Time Systems
ABB AB, Västerås, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-3242-6113
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0002-3210-3819
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1364-8127
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2021 (English)In: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, Institute of Electrical and Electronics Engineers Inc. , 2021Conference paper, Published paper (Refereed)
Abstract [en]

Many real-time applications have functional behaviour that requires variability in timing properties at runtime. The elastic task model provides a convenient mechanism to specify and encapsulate such variability and enables the modification of an application's periods during run-time to keep the application schedulable. Additionally, reservation-based scheduling techniques were proposed for the same purpose of taming unpredictability of timing variations, but with a different solution, i.e., by providing the spatial and temporal isolation for executing independent applications on the same hardware. In this paper, we combine the two approaches by proposing a two-level adaptive scheduling framework which is based on the elastic task model and the compositional framework based on the periodic resource model. The proposed framework minimises the number of requests for bandwidth adaption at the reservation (system) level and primarily enables schedulability by accounting for the application's elasticity by adjusting the periods. The motivation for this design choice is to rather localise the effect of the modifications within the application, without necessarily affecting all the applications at the system level compared to the changes made at the application level. The evaluation results show that the local application changes may often be enough to solve the problem of variability, significantly reducing the number of bandwidth adjustments, and therefore reducing the potential negative impact on all the applications of a system.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2021.
Keywords [en]
Elastic task model, Hierarchical scheduling, Real-time, Reservations, Hierarchical systems, Interactive computer systems, Real time systems, Scheduling, Elastic applications, Elastic tasks, Real - Time system, Real- time, Reservation, Runtimes, System levels, Task modelling, Bandwidth
National Category
Control Engineering Embedded Systems
Identifiers
URN: urn:nbn:se:mdh:diva-57101DOI: 10.1109/ETFA45728.2021.9613375ISI: 000766992600094Scopus ID: 2-s2.0-85122971525ISBN: 9781728129891 (print)OAI: oai:DiVA.org:mdh-57101DiVA, id: diva2:1640420
Conference
26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021, 7 September 2021 through 10 September 2021
Available from: 2022-02-24 Created: 2022-02-24 Last updated: 2022-11-08Bibliographically approved
In thesis
1. Integrating Elastic Real-Time Applications on Fog Computing Platforms
Open this publication in new window or tab >>Integrating Elastic Real-Time Applications on Fog Computing Platforms
2022 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Real-time systems such as industrial robots and autonomous navigation vehicles integrate a wide range of algorithms to achieve their functional behavior. In certain systems, these algorithms are deployed on dedicated single-core hardware platforms that exchange information over a real-time network. With the availability of current multi-core platforms, there is growing interest in an integrated architecture where these algorithms can run on a shared hardware platform. In addition, the benefits of virtualization-based cloud and fog architectures for non-real-time applications have prompted discussions about the possibility of achieving similar benefits for real-time systems. Although many useful solutions such as resource reservations and hierarchical scheduling have been proposed to facilitate hardware virtualization for real-time applications, the current state of the art is mainly concerned with applications whose timing requirements can be modelled according to the periodic or the sporadic task model. Since the computational demand of many real-time algorithms can be flexibly adjusted at runtime, e.g., by changing the periods, they can be better abstracted with the elastic task model in the context of virtualized hardware platforms.

Therefore, in this thesis, we first propose a scheduling framework with reservations based on periodic resource supply for real-time elastic applications with single-core workloads, and then extend this solution for applications with multi-core workloads  where reservations are based on the minimum-parallelism model. Since many existing applications run on dedicated single-core platforms, we simultaneously provide a systematic methodology for migrating an existing real-time software application from a single-core to a multi-core platform. In doing so, we focus on recovering the architecture of the existing software and transforming it for implementation on a multi-core platform. Next, we explore the advantages of a fog-based architecture over an existing robot control architecture and identify the key research challenges that must be addressed for the adoption of the fog computing architecture.

Place, publisher, year, edition, pages
Mälardalens universitet, 2022
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 321
National Category
Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-57512 (URN)978-91-7485-547-0 (ISBN)
Presentation
2022-03-30, Delta, Mälardalens universitet, Västerås, 14:00 (English)
Opponent
Supervisors
Available from: 2022-03-01 Created: 2022-02-28 Last updated: 2022-11-08Bibliographically approved

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Salman Shaik, MohammadMubeen, SaadMarkovic, FilipPapadopoulos, AlessandroNolte, Thomas

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