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A resource efficient framework to run automotive embedded software on multi-core ECUs
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1384-5323
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-3375-6766
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-5297-6548
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-6132-7945
(Swedish)Manuscript (preprint) (Other academic)
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-36448OAI: oai:DiVA.org:mdh-36448DiVA: diva2:1142127
Available from: 2017-09-18 Created: 2017-09-18 Last updated: 2017-09-18Bibliographically approved
In thesis
1. Resource Optimization in Multi-processor Real-time Systems
Open this publication in new window or tab >>Resource Optimization in Multi-processor Real-time Systems
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis addresses the topic of resource efficiency in multiprocessor systems in the presence of timing constraints. 

 Nowadays, almost wherever you look, you find a computing system. Most computing systems employ a multiprocessor platform. Multiprocessor systems can be found in a broad spectrum of computing systems ranging from a tiny chip hosting multiple cores to large geographically-distributed cloud data centers connected by the Internet. In multiprocessor systems, efficient use of computing resources is a substantial element when it comes to achieving a desirable performance for running software applications. 

 Most industrial applications, e.g., automotive and avionics applications, are subject to a set of real-time constraints that must be met. Such kinds of applications, along with the underlying hardware and software components running the application, constitute a real-time system. In real-time systems, the first and major concern of the system designer is to provide a solution where all timing constraints are met. Therefore, in multiprocessor real-time systems, not only resource efficiency, but also meeting all the timing requirements, is a major concern. 

 Industrie 4.0 is the current trend in automation and manufacturing when it comes to creating next generation of smart factories. Two categories of multiprocessor systems play a significant role in the realization of such a smart factory: 1) multi-core processors which are the key computing element of embedded systems, 2) cloud computing data centers as the supplier of a massive data storage and a large computational power. Both these categories are considered in the thesis, i.e., 1) the efficient use of embedded multi-core processors where multiple processors are located on the same chip, applied to execute a real-time application, and 2) the efficient use of multi-processors within a cloud computing data center. We address these two categories of multi-processor systems separately. 

 For each of them, we identify the key challenges to achieve a resource-efficient design of the system. We then formulate the problem and propose optimization solutions to optimize the efficiency of the system, while satisfying all timing constraints. Introducing a resource efficient solution for those two categories of multi-processor systems facilitates deployment of Industrie 4.0 in smart manufacturing factories where multi-core embedded processors and cloud computing data centers are two central cornerstones.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2017
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 263
National Category
Computer Science
Identifiers
urn:nbn:se:mdh:diva-35387 (URN)978-91-7485-336-0 (ISBN)
Presentation
2017-10-05, Paros, Mälardalens högskola, Västerås, 13:30 (English)
Opponent
Supervisors
Available from: 2017-09-14 Created: 2017-05-24 Last updated: 2017-09-29Bibliographically approved

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CiteExportLink to record
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  • apa
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