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Configuration Management for Proactive Adaptation in Pervasive Environments
VanSyckel, Sebastian
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Schäfer, Dominik
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Schiele, Gregor
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Becker, Christian
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DOI:
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https://doi.org/10.1109/SASO.2013.28
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URL:
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https://www.insight-centre.org/sites/default/files...
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Additional URL:
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http://dl.acm.org/citation.cfm?id=2552639.2552644
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Document Type:
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Conference or workshop publication
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Year of publication:
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2013
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Book title:
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2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2013) : Philadelphia, Pennsylvania, USA, 9 - 13 September 2013
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Page range:
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131-140
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Conference title:
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IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2013)
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Location of the conference venue:
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Philadelphia, Pa.
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Date of the conference:
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9-13 September 2013
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Place of publication:
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Piscataway, NJ
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Publishing house:
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IEEE Computer Soc.
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ISBN:
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978-0-7695-5129-6 , 978-1-4799-1452-4
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ISSN:
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1949-3673
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Publication language:
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English
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Institution:
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Business School > Wirtschaftsinformatik II (Becker 2006-2021)
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Subject:
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004 Computer science, internet
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Keywords (English):
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configuration management , constraint satisfaction problems , biquitous computing , CSP adaption delay reduction application model , configuration management , constraint satisfaction problem , cost functions , cost metrics
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Abstract:
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Pervasive computing applications have to adapt in order to cope with changes in their environment. Proactive adaptation allows to change the application and/ or the context based on prediction of context and user behavior, in order to reduce adaption delay and provide a seamless service to the user. Thus, such applications are self-organizing systems. Ideally, self-organizing systems adapt by changing their structure or behavior without requiring the user's intervention. A prerequisite to that is the knowledge of the possible configurations and their order with respect to the suitability. We introduce a comprehensive framework based on an application model with suitability and cost metrics. Based on the application model, we construct a CSP and develop an algorithm with two heuristics that finds all configurations. We rate the configurations depending on their expected instantiation using novel utility and cost functions. In the evaluation, we show the feasibility of our approach.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
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