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Hardware/Software Partitioning Methodology for Embedded Applications using Multiple Criteria Decision Analysis
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-6954-8339
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: urn:nbn:se:mdh:diva-33210ISBN: 978-91-7485-284-4 (print)OAI: oai:DiVA.org:mdh-33210DiVA, id: diva2:972795
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
List of papers
1. Modelling for Hardware and Software Partitioning based on Multiple Properties
Open this publication in new window or tab >>Modelling for Hardware and Software Partitioning based on Multiple Properties
2013 (English)In: Proceedings - 39th Euromicro Conference Series on Software Engineering and Advanced Applications, SEAA 2013, 2013, p. 189-194Conference paper, Published paper (Refereed)
Abstract [en]

In many embedded systems types the separation process for deploying the applications as software and hardware executable units, called partitioning is crucial. This is due to the fact that partitioning decisions impact the overall life cycle of the systems. In industry it is common practice to take partitioning decisions in an early stage of the design, based on hardware and software designers expertise. We propose a new methodology as a combination of modelbased and component-based approaches which enables a late partitioning decisions based on high level system requirements and project constrains. The final partitioning is decided based on a multi-property analysis approach. Here, we focus on the formalization of the overall process and in particular on the definition of a comprehensive system metamodel. This is meant to support modelling approaches suitable for enabling both the partitioning and reuse. An industrial case study is used to illustrate the approach.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:mdh:diva-22262 (URN)10.1109/SEAA.2013.56 (DOI)2-s2.0-84889055176 (Scopus ID)978-0-7695-5091-6 (Local ID)978-0-7695-5091-6 (Archive number)978-0-7695-5091-6 (OAI)
Conference
39th Euromicro Conference Series on Software Engineering and Advanced Applications, SEAA 2013; Santander; Spain; 4 September 2013 through 6 September 2013
Projects
ITS-EASY Post Graduate School for Embedded Software and Systems
Available from: 2013-11-03 Created: 2013-10-31 Last updated: 2016-09-22Bibliographically approved
2. Architectural Decisions for HW/SW Partitioning Based on Multiple Extra-Functional Properties
Open this publication in new window or tab >>Architectural Decisions for HW/SW Partitioning Based on Multiple Extra-Functional Properties
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Growing advances in hardware technologies are enabling significant improvements in application performance by the deployment of components to dedicated executable units. This is particularly valid for Cyber Physical Systems in which the applications are partitioned in HW and SW execution units. The growing complexity of such systems, and increasing requirements, both project- and product-related, makes the partitioning decision process complex. Although different approaches to this decision process have been proposed during recent decades, they lack the ability to provide relevant decisions based on a larger number of requirements and project/business constraints. A sound approach to this problem is taking into account all relevant requirements and constraints and their relations to the properties of the components deployed either as HW or SW units. A typical approach for managing a large number of criteria is a multicriteria decision analysis. This, in its turn, requires uniform definitions of component properties and their realization in respect to their HW/SW deployment. The aim of this paper is twofold: a) to provide an architectural metamodel of component-based applications with specifications of their properties with respect to their partitioning, and b) to categorize component properties in relation to HW/SW deployment. The metamodel enables the transition of system requirements to system and component properties. The categorization provides support for architectural decisions. It is demonstrated through a property guideline for the partitioning of the System Automation and Control domain. The guideline is based on interviews with practitioners and researchers, the experts in this domain.

National Category
Engineering and Technology Other Engineering and Technologies
Identifiers
urn:nbn:se:mdh:diva-24957 (URN)10.1109/WICSA.2014.19 (DOI)2-s2.0-84903702504 (Scopus ID)978-1-4799-3412-6 (ISBN)
Conference
11th Working IEEE/IFIP Conference on Software Architecture (WICSA 2014), Sydney, Australia, April 7-11, 2014
Projects
ITS-EASY
Available from: 2014-05-06 Created: 2014-05-06 Last updated: 2016-09-22Bibliographically approved
3. On applying multiple criteria decision analysis in embedded systems design
Open this publication in new window or tab >>On applying multiple criteria decision analysis in embedded systems design
2016 (English)In: Design automation for embedded systems, ISSN 0929-5585, E-ISSN 1572-8080, Vol. 20, p. 211-238Article 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
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-33207 (URN)10.1007/s10617-016-9171-7 (DOI)000381991300003 ()2-s2.0-84958772469 (Scopus ID)
Available from: 2016-09-22 Created: 2016-09-22 Last updated: 2017-11-21Bibliographically approved
4. Extra-Functional Properties Composability for Embedded Systems Partitioning
Open this publication in new window or tab >>Extra-Functional Properties Composability for Embedded Systems Partitioning
2016 (English)In: Proceedings - 2016 19th International ACM SIGSOFT Symposium on Component-Based Software Engineering, CBSE 2016, 2016, p. 69-78Conference paper, Published paper (Refereed)
Abstract [en]

Modern embedded systems utilize the advances in heterogeneous platforms that enable implementing functions in software (SW) and hardware (HW) components. A proper configuration of SW and HW components can significantly improve the values of the extra-functional properties such as performance and energy savings. However, due to increasing application complexity, it is difficult to find the best combination of HW and SW components. The problem basically boils down to calculate, for a given architecture, the system properties from the components' ones. In this paper, we address the problem of composability of EFPs at system level. Although in general this is not a solvable problem, we present that, under strictly specified constraints, it is possible to compose the system EFPs starting from the component ones. We start by detailing constraints related to the system architecture, platform and process development and, based on these constraints, we provide composition rules for different types of EFPs. We demonstrate the results through an industrial example.

Keywords
Composability, Embedded Systems, Extra-Functional Properties, Partitioning, Computer architecture, Energy conservation, Problem solving, Software engineering, Application complexity, Heterogeneous platforms, Modern embedded systems, System architectures, Systems partitioning
National Category
Embedded Systems
Identifiers
urn:nbn:se:mdh:diva-32912 (URN)10.1109/CBSE.2016.19 (DOI)000390946500009 ()2-s2.0-84981485900 (Scopus ID)9781509025695 (ISBN)
Conference
19th International ACM SIGSOFT Symposium on Component-Based Software Engineering, CBSE 2016, 5 April 2016 through 8 April 2016
Available from: 2016-08-25 Created: 2016-08-25 Last updated: 2017-01-26Bibliographically approved
5. Methodology for Embedded Systems Partitioning based on Multiple Criteria Decision Analysis
Open this publication in new window or tab >>Methodology for Embedded Systems Partitioning based on Multiple Criteria Decision Analysis
2016 (English)Report (Other academic)
Abstract [en]

Platforms with different computation resource, e.g. CPUs and FPGAs, known as heterogeneous platforms, are becoming one of the first choices to deploy performance-requiring embedded applications. On this technology, functionalities can be implemented either as hardware (HW) or software (SW) components. In this paper, we propose a new methodology, called MultiPar, which is able to provide optimal partitioning solution(s) with respe system properties based on Multiple Criteria Decision Analysis. We provide an overview of the methodology. MultiPar is based on a bottom-up principle, first, to find the most suitable SW and HW implementations based on their properties, and then applying compositional rules and other means uses the system properties to find the best partitioning solutions. In addition, we show the feasibility of the proposed methodology through an industrial case, and in particular validation of the compositional rules for some properties used in the partitioning decision process. MultiPar methodology is implemented as a tool, which is used in the validation process.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-33208 (URN)
Available from: 2016-09-22 Created: 2016-09-22 Last updated: 2016-12-13Bibliographically approved
6. Inclusion of Ethical Aspects in Multi-criteria Decision Analysis
Open this publication in new window or tab >>Inclusion of Ethical Aspects in Multi-criteria Decision Analysis
2016 (English)In: Proceedings - 2016 1st International Workshop on Decision Making in Software ARCHitecture, MARCH 2016, 2016, p. 1-8Conference paper, Published paper (Refereed)
Abstract [en]

Decision process is often based on multi-faceted and mutually opposing criteria. In order to provide rigorous techniques for problem structuring and criteria aggregation used for classification and ranking of alternatives, Multiple Criteria Decision Analysis (MCDA) has been used as a method to achieve architectural decisions. Even though it has already been argued in literature that MCDA essentially depends on value systems of decision-makers, it is a question how the decision result reflects a particular criterion, requirement or a particular decision. This is especially true if a criterion is not precisely specified. In this paper we analyse the ethical aspects of MCDA. In our analysis we argue that it is in the long run necessary to make value basis of decision-making and ethical considerations explicit and subject for scrutiny. As a support to encourage introduction of transparent value-based deliberation we propose an extended MCDA scheme that would explicitly take into account ethical analysis. As an illustration, we present an industrial case study for the Software (SW)/Hardware (HW) partitioning of a wind turbine application in which different decisions can be taken, depending on the ethical aspects. 

Keywords
Embedded Systems, Ethical Aspects, Ethics, Multiple Criteria Decision Analysis, Application programs, Decision theory, Operations research, Philosophical aspects, Software architecture, Wind turbines, Architectural decision, Ethical considerations, Industrial case study, Multi-criteria decision analysis, Ranking of alternatives, Decision making
National Category
Embedded Systems
Identifiers
urn:nbn:se:mdh:diva-32524 (URN)10.1109/MARCH.2016.8 (DOI)000382526100001 ()2-s2.0-84979519277 (Scopus ID)9781509025732 (ISBN)
Conference
1st International Workshop on Decision Making in Software ARCHitecture, MARCH 2016, 5 April 2016
Available from: 2016-08-18 Created: 2016-08-18 Last updated: 2016-09-29Bibliographically approved

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