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Bio-inspired error detection for complex systems
Leibniz University of Hannover.
University of York.ORCID iD: 0000-0003-2415-8219
University of York.
2011 (English)In: Proceedings of IEEE Pacific Rim International Symposium on Dependable Computing, PRDC, 2011, 154-163 p.Conference paper (Refereed)
Abstract [en]

In a number of areas, for example, sensor networks and systems of systems, complex networks are being used as part of applications that have to be dependable and safe. A common feature of these networks is they operate in a de-centralised manner and are formed in an ad-hoc manner and are often based on individual nodes that were not originally developed specifically for the situation that they are to be used. In addition, the nodes and their environment will have different behaviours over time, and there will be little knowledge during development of how they will interact. A key challenge is therefore how to understand what behaviour is normal from that which is abnormal so that the abnormal behaviour can be detected, and be prevented from affecting other parts of the system where appropriate recovery can then be performed. In this paper we review the state of the art in bio-inspiredapproaches, discuss how they can be used for error detection as part of providing a safe dependable sensor network, and then provide and evaluate an efficient and effective approach to error detection.

Place, publisher, year, edition, pages
2011. 154-163 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-23830DOI: 10.1109/PRDC.2011.27ISI: 000305062200018Scopus ID: 2-s2.0-84857744693ISBN: 978-076954590-5 OAI: oai:DiVA.org:mdh-23830DiVA: diva2:682483
Conference
17th Pacific Rim International Symposium on Dependable Computing (PRDC), 2011 IEEE
Available from: 2013-12-27 Created: 2013-12-19 Last updated: 2014-05-16Bibliographically approved

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Cite
Citation style
  • apa
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Language
  • de-DE
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  • nn-NB
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Output format
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