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Context-Aware Adaptation in DySCAS
University of Greenwich.
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Control Systems.ORCID iD: 0000-0001-7048-0108
University of Greenwich.
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Control Systems.
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2009 (English)In: Electronic Communications of the EASST, ISSN 1863-2122, E-ISSN 1863-2122, ISSN 1863-2122, Vol. 19Article in journal (Refereed) Published
Abstract [en]

DySCAS is a dynamically self-configuring middleware for automotivecontrol systems. The addition of autonomic, context-aware dynamic configurationto automotive control systems brings a potential for a wide range of benefits in termsof robustness, flexibility, upgrading etc. However, the automotive systems representa particularly challenging domain for the deployment of autonomics concepts, havinga combination of real-time performance constraints, severe resource limitations,safety-critical aspects and cost pressures. For these reasons current systems are staticallyconfigured. This paper describes the dynamic run-time configuration aspectsof DySCAS and focuses on the extent to which context-aware adaptation has beenachieved in DySCAS, and the ways in which the various design and implementationchallenges are met.

Place, publisher, year, edition, pages
Berlin: European Association of Software Science and Technology (EASST) , 2009. Vol. 19
Keyword [en]
real-time embedded systems, dynamic configuration, context-aware behaviour, automotive control, middleware, policy-based configuration
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:kth:diva-79855DOI: 10.14279/tuj.eceasst.19.245OAI: oai:DiVA.org:kth-79855DiVA: diva2:495767
Conference
Second International DisCoTec Workshop on Context-aware Adaptation Mechanisms for Pervasive and Ubiquitous Services (CAMPUS 2009). Lisbon, Portugal. June 12 2009
Note

QC 20120502

Available from: 2012-02-09 Created: 2012-02-09 Last updated: 2017-12-07Bibliographically approved

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Chen, DeJiuTörngren, Martin

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