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On applying multiple criteria decision analysis in embedded systems design
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-6954-8339
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1996-1234
2016 (English)In: Design automation for embedded systems, ISSN 0929-5585, E-ISSN 1572-8080, Vol. 20, 211-238 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer, 2016. Vol. 20, 211-238 p.
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-33207DOI: 10.1007/s10617-016-9171-7ISI: 000381991300003Scopus ID: 2-s2.0-84958772469OAI: oai:DiVA.org:mdh-33207DiVA: diva2:972786
Available from: 2016-09-22 Created: 2016-09-22 Last updated: 2016-10-31Bibliographically approved
In thesis
1. Hardware/Software Partitioning Methodology for Embedded Applications using Multiple Criteria Decision Analysis
Open this publication in new window or tab >>Hardware/Software Partitioning Methodology for Embedded Applications using Multiple Criteria Decision Analysis
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The new hardware technologies enable execution of embedded systems applications on heterogeneous execution platforms. These platforms consist of different execution processing units, for example of CPUs, and FPGAs, that enable the application execution of software (SW) components, typically implemented as C/C++ code, and hardware (HW) components, implemented as VHDL code. This heterogeneity enables building dedicated components which can significantly improve the application performance. This, however, requires decisions on which components will be implemented as SW and which as HW execution units. This decision process in known as HW/SW partitioning, and is a subject of research of more than 20 years. Typical goals of this research was to find the optimal partitioning with respect to the system performance, and possibly a couple of other properties such as power consumption, or resource utilization (e.g. related to CPU memory footprint and FPGA area). However, by significant increase in complexity of the applications, and inclusion of different requirements, the partitioning decisions become more complex, as well as the entire development process with an integrated partitioning decision process. Today there is a lack of a systematic approach for partitioning complex applications. This thesis addresses this challenge. The main objective of the thesis is to design and build a systematic partitioning decision process that includes many requirements of different types. The thesis describes a new method MULTIPAR that includes the partitioning decision process for component-based embedded systems. The method is based on model-based engineering principles; components are analysed as models which can be implemented either as a SW or HW components, and the implementation itself is performed at a late stage of the development process. The partition is based on the optimisation of the application’s and components’ extra-functional properties (EFPs) that are derived from the requirements and project constraints. For the optimization a Multiple Criteria Decision Analysis (MCDA) method is used. As a part of the main contribution, the thesis includes several independent contributions that are of a more general character: a) modeling principles for component-based applications which consists of SW and HW components, and a component can be implemented as SW or/and HW code; b) a classification and analysis of EFPs in respect to the dependency on their HW or SW implementation; c) composition rules for some of EFPs for SW and HW components; d) suitability and limitations of MCDA methods in their usage for the partitioning decisions. MULTIPAR is also implemented in a form of a tool that enables a selection of components and analysis of the system in respect to the selected EFPs. The feasibility of MULTIPAR was validated through two industrial cases. The thesis is organized in two parts; the first part includes an introduction summarizing the overall work and discussing the research approach, and the second part collect the most relevant papers published in different venues.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2016
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 210
National Category
Embedded Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-33210 (URN)978-91-7485-284-4 (ISBN)
Public defence
2016-11-04, Lambda, Mälardalens högskola, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2016-09-23 Created: 2016-09-22 Last updated: 2016-09-23Bibliographically approved

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