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Autonomic Middleware for Automotive Embedded Systems
The University of Greenwich.
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Systems.ORCID iD: 0000-0001-7048-0108
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Systems.ORCID iD: 0000-0002-4300-885X
Enea Data AB.
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2009 (English)In: Autonomic Communication / [ed] Vasilakos, Athanasios V.; Parashar, Manish; Karnouskos, Stamatis; Pedrycz, Witold, Springer US , 2009, 169-210 p.Chapter in book (Refereed)
Abstract [en]

This chapter describes DySCAS: an advanced autonomic platform-independent middleware framework for automotive embedded systems. The concepts and architecture are motivated and described in detail, focusing on the need for, and achievement of, high flexibility and automatic run-time reconfiguration. The design of the middleware is positioned with respect to the way it overcomes the specific technical, environmental, and performance challenges of the automotive domain. Self-management is achieved in terms of automatic configuration for context-aware behavior, resource-use efficiency, and self-healing to handle run-time detected faults. The self-management is governed by the use of policies distributed throughout the middleware components. The simulation techniques that have been used for extensive validation are described and some key results presented. A reference implementation is presented, illustrating the way in which the various concepts and mechanisms can be realized and orchestrated.

Place, publisher, year, edition, pages
Springer US , 2009. 169-210 p.
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:kth:diva-79465DOI: 10.1007/978-0-387-09753-4Scopus ID: 2-s2.0-77954732080ISBN: 978-0-387-09752-7 (print)OAI: oai:DiVA.org:kth-79465DiVA: diva2:495534
Note
QC 20120214Available from: 2012-02-09 Created: 2012-02-09 Last updated: 2012-02-14Bibliographically approved

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Publisher's full textScopushttp://dx.doi.org/10.1007/978-0-387-09753-4_7

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Chen, DeJiuTörngren, MartinFeng, Lei

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