On applying multiple criteria decision analysis in embedded systems design

We focus here on the application of multi critera decision analysis (MCDA) techniques in hardware/software partitioning activities to be used in the design and deployment of embedded systems. Our goal is to identify the best existing methods and tools suitable to support the approach we have taken f...

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Published inDesign automation for embedded systems Vol. 20; no. 3; pp. 211 - 238
Main Authors Sapienza, Gaetana, Brestovac, Goran, Grgurina, Robi, Seceleanu, Tiberiu
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2016
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ISSN0929-5585
1572-8080
1572-8080
DOI10.1007/s10617-016-9171-7

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Abstract We focus here on the application of multi critera decision analysis (MCDA) techniques in hardware/software partitioning activities to be used in the design and deployment of embedded systems. Our goal is to identify the best existing methods and tools suitable to support the approach we have taken for the partitioning process. We provide this via a survey of the most well-known MCDA methods and tools (for a specific class of MCDA methods called multi attribute decision making. We identify a set of criteria that need to be addressed, in some way, by the methods, and implemented by related tools. These “11-suitability criteria” help us in deciding the appropriateness of the analysed methods and tools for the envisaged partitioning approach. In brief, we are interested that the MCDA methods are taking into account multiple extra-functional properties, expressed by a variety of types, with possible missing values, should enable dependency handling, decision traceability, etc. The conclusion is that there are criteria that are not fulfilled by any of the methods, and hence there is no method or tool that can directly used for the partitioning. However, the results shows the potential of using MCDA in the partitioning process and provide a good starting point for future research activities.
AbstractList We focus here on the application of multi critera decision analysis (MCDA) techniques in hardware/software partitioning activities to be used in the design and deployment of embedded systems. Our goal is to identify the best existing methods and tools suitable to support the approach we have taken for the partitioning process. We provide this via a survey of the most well-known MCDA methods and tools (for a specific class of MCDA methods called multi attribute decision making. We identify a set of criteria that need to be addressed, in some way, by the methods, and implemented by related tools. These “11-suitability criteria” help us in deciding the appropriateness of the analysed methods and tools for the envisaged partitioning approach. In brief, we are interested that the MCDA methods are taking into account multiple extra-functional properties, expressed by a variety of types, with possible missing values, should enable dependency handling, decision traceability, etc. The conclusion is that there are criteria that are not fulfilled by any of the methods, and hence there is no method or tool that can directly used for the partitioning. However, the results shows the potential of using MCDA in the partitioning process and provide a good starting point for future research activities.
Author Sapienza, Gaetana
Grgurina, Robi
Brestovac, Goran
Seceleanu, Tiberiu
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Issue 3
Keywords Deployment
Embedded systems design methodology
Multi-criteria decision analysis (MCDA)
Multi attribute decision making (MADM) partitioning
Language English
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Snippet We focus here on the application of multi critera decision analysis (MCDA) techniques in hardware/software partitioning activities to be used in the design and...
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SubjectTerms CAE) and Design
Circuits and Systems
Computer-Aided Engineering (CAD
Engineering
Special Purpose and Application-Based Systems
Title On applying multiple criteria decision analysis in embedded systems design
URI https://link.springer.com/article/10.1007/s10617-016-9171-7
https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-33207
Volume 20
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