DAACS : a Decision Approach for Autonomic Computing Systems.
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| Title: | DAACS : a Decision Approach for Autonomic Computing Systems. |
|---|---|
| Authors: | Abdennadher, Imen1 (AUTHOR) imen.abdennadher@redcad.org |
| Source: | Journal of Supercomputing. Feb2022, Vol. 78 Issue 3, p3883-3904. 22p. |
| Subjects: | Autonomic computing, Computer systems, Intelligent buildings |
| Abstract: | Systems running in ubiquitous environments are characterized by a context that changes frequently. The adaptation of this kind of systems according to the context is a complex task. Autonomic computing has received a great attention as a solution for this increasing complexity, through an architecture based on the MAPE-K loop. Decisions within the phases of the MAPE-K loop have an important impact on the success of systems adaptation. In the literature, many research activities propose decision approaches and frameworks for autonomic applications adaptation. Nevertheless, there is a lack of guidelines for the adaptation decisions design task. In this work, we propose a Decision Approach for Autonomic Computing Systems, called DAACS, which includes recommendations and steps that should be followed by the autonomic applications designers. DAACS was implemented in a Smart Building case study, and it was evaluated in term of the processing time dedicated for the adaptation decisions. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 155105907 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: DAACS : a Decision Approach for Autonomic Computing Systems. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Abdennadher%2C+Imen%22">Abdennadher, Imen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> imen.abdennadher@redcad.org</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>. Feb2022, Vol. 78 Issue 3, p3883-3904. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Autonomic+computing%22">Autonomic computing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+systems%22">Computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligent+buildings%22">Intelligent buildings</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Systems running in ubiquitous environments are characterized by a context that changes frequently. The adaptation of this kind of systems according to the context is a complex task. Autonomic computing has received a great attention as a solution for this increasing complexity, through an architecture based on the MAPE-K loop. Decisions within the phases of the MAPE-K loop have an important impact on the success of systems adaptation. In the literature, many research activities propose decision approaches and frameworks for autonomic applications adaptation. Nevertheless, there is a lack of guidelines for the adaptation decisions design task. In this work, we propose a Decision Approach for Autonomic Computing Systems, called DAACS, which includes recommendations and steps that should be followed by the autonomic applications designers. DAACS was implemented in a Smart Building case study, and it was evaluated in term of the processing time dedicated for the adaptation decisions. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11227-021-04011-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 3883 Subjects: – SubjectFull: Autonomic computing Type: general – SubjectFull: Computer systems Type: general – SubjectFull: Intelligent buildings Type: general Titles: – TitleFull: DAACS : a Decision Approach for Autonomic Computing Systems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Abdennadher, Imen IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 02 Text: Feb2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 09208542 Numbering: – Type: volume Value: 78 – Type: issue Value: 3 Titles: – TitleFull: Journal of Supercomputing Type: main |
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