=Paper=
{{Paper
|id=Vol-2405/04_paper
|storemode=property
|title=A-CPS: Automation in High-performance Cyber Physical Systems Development
|pdfUrl=https://ceur-ws.org/Vol-2405/04_paper.pdf
|volume=Vol-2405
|authors=Alessio Bucaioni
|dblpUrl=https://dblp.org/rec/conf/staf/Bucaioni19
}}
==A-CPS: Automation in High-performance Cyber Physical Systems Development==
https://ceur-ws.org/Vol-2405/04_paper.pdf
A-CPS: Automation in High-performance Cyber
Physical Systems Development
Alessio Bucaioni
School of Innovation, Design and Engineering
Mälardalen University, Sweden
{name.surname}@mdh.se
Abstract. In this paper, we describe the Automation in High-performance Cy-
ber Physical Systems Development research project. Its main goal is to con-
tribute to the advancement of the state of the art in the model-based develop-
ment of heterogeneous vehicular systems. In particular, the project aims at pro-
viding a model-based framework for the automatic assessment of timeliness of
vehicular systems by means of model-based simulation, timing analysis and their
interplay. Additional information on the project can be found through its offi-
cial website: http://www.es.mdh.se/projects/520-Automation_
in_High_performance_Cyber_Physical_Systems_Development
Keywords: Model-based software development, cyber physical systems, hetero-
geneous platforms, model-based timing verification.
1 Introduction
High-performance cyber-physical systems (CPS), like autonomous vehicles, are bring-
ing computing into the new era of heterogeneous computing, where all the future com-
puting platforms are likely to have several different computational units [13]. However,
when different computing architectures are put together, one main challenge is to cope
use the enormous computing capabilities, while still meeting several non functional cri-
teria like timeliness and performance, to name a few. In particular, timeliness and its
verification are of crucial importance for modern vehicles as they impact their safety
and customer value. In order to tackle this challenge, the engineers not only need to
write parallel software, but also cope with issues introduced by heterogeneity and par-
allelism, such as allocation of computations to computational units, that is an extremely
complex task as it involves investigating the whole design space of possible alloca-
tions, which is typically infeasible without automation support. Today, at the best of our
knowledge, there is little to no support for automating this task in the high-performance
CPS development and these activities are mostly done manually, which makes them
tedious, error-prone and inefficient. In this context, we believe that model-based tech-
niques, such as modelling and model transformations, can be game changers in the
development of high-performance CPS and particularly in supporting automatic timing
verification [4]. Models could be employed for representing the software architecture
and its timing-related properties while abstracting away from platform-specificity [3].
Model transformations could provide automation for the generation and optimisation of
the design space of possible allocations [14]. This paper describes how the Automation
in High-performance Cyber Physical Systems Development (A-CPS) research project
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
16 Alessio Bucaioni
contributes in tackling the challenge of introducing automation into the development
of high-performance vehicular systems for providing automatic assessment of timing.
A-CPS is a two year Swedish research project started in April 2019 and includes one
academic partner, Mälardalen University (MDH), and two business partners, Arcticus
Systems AB (AS) and Volvo Group Trucks Technologies (VGTT). A-CPS is funded by
MDH, AS, VGTT and the Swedish Knowledge Foundation1 (KKS) for a total of 1 893
776 Swedish kronor.
2 Project Team
The project team consists of three partners, namely MDH, AS and VGTT, which pro-
vide complementary competences in their respective domains. MDH is a world-leading
university in the field of real-time systems research. The team from MDH includes the
project leader, Dr. Alessio Bucaioni, and the reference group members namely Prof.
Marjan Sirjani, Assoc. Prof. Cristina Seceleanu and Assoc. Prof. Patrizio Pellicione as
external member from the Chalmers University of Technology (CTH) and University
of Gothenburg (GU). Dr. Alessio Bucaioni has gained deep theoretical and practical
background in model-driven engineering of embedded systems, especially regarding
domain-specific modelling languages and automatic manipulations of system models
for analysis purposes [4]. The research within A-CPS is conducted in the Industrial
Software Engineering group headed by Prof. Jan Carlson. AS is a leading tool vendor
for model-based software development of real-time embedded systems. It specialises
in the vehicular domain and its tools have been used by the industry for over twenty
years by world leading companies such as, e.g., Volvo Construction Equipment, BAE
Systems, etc. AS contributes to A-CPS by supplying industrial needs, requirements
and commercial tools. Dr. Kurt-Lennart Lundbäck represents AS in A-CPS. He is the
founder and CEO of the company and his vast industrial experience and great expertise
in real-time embedded systems and timing analysis bring an invaluable contribution to
A-CPS. VGTT is the second-largest heavy-duty truck manufacturer in the world with
heavy vehicles sold and serviced in more than 140 countries all over the world under
several brands. The VGTT products are increasingly defined by software, and software
related research and development is in strong growth within the company. In addition,
the company has been successfully applying model-based software development to pro-
vide computer-control functionality in the vehicles for several years. VGTT contributes
to A-CPS by supplying industrial needs, requirements and use cases. It contributes by
proving the efficiency of the methods, techniques and results in the industrial setting,
too. Dr. Henrik Lönn represents VGTT in A-CPS. He is an embedded software spe-
cialist with valuable experience and expertise as coordinator in national and European
research projects.
3 Research Plan
In this section, we describe the A-CPS research goal, challenges, time plan, research
methodology and expected outcomes.
1
https://www.kks.se
A-CPS: Automation in High-performance Cyber Physical Systems Development 17
3.1 Research Goal
The main goal of A-CPS is to provide a model-based framework for providing auto-
matic assessment of timing for vehicular systems by means of model-based simulation,
model-based timing analysis and their interplay. The proposed framework uses domain-
specific modelling languages for representing the software architectures and its tim-
ing properties in terms structural and behavioural models. These models are platform-
agnostic and do not carry allocation information. Model transformation translate these
models into models ready for simulation and timing analysis. Such a translation in-
volves the generation of models enriched with allocation information and it allows to
exploit the computational power of heterogeneous platform while providing an auto-
matic solution to the allocation challenge. Eventually, the observed results from the
simulation and analysis are used for ensuring timing compliance of the vehicular sys-
tem under development. As we aim at transferring the A-CPS results to industrial pro-
cesses, the proposed framework leverages commercial and open-source languages as
well as tools used in the vehicular segment. In particular, the modelling activities relies
on the de-facto standard vehicular-specific modelling languages EAST-ADL [2] and
AUTOSAR [1] and the commercial modelling language Rubus Component Model [8]
(RCM). The timing analysis and simulation are carried out within the RCM integrated
development environment, Rubus ICE, and the Eclipse Modelling Framework based
tools Artop/EATOP, respectively.
3.2 Research Challenges
Towards the fulfilment of the project goal, we identify the following research challenges
(RCs) to be tackled.
RC1: Modelling of software architecture and timing-related properties. As we
leverage commercial and open-source modelling languages, the challenge is to investi-
gate how to extend these languages without disrupting their technological assets.
RC2: Automation for assessment of timeliness. We want to monitor the timing-
compliance of the vehicular system earlier in the development process and employ the
observed values for taking evidence-based design decisions. To this end, the models of
the software architecture and its timing-related properties must be enriched with alloca-
tion information and translated into models ready for the model-based simulation and
analysis. This challenge can be broken down into three sub-challenges.
RC2.1: Automation for simulation-based assessment of timeliness. The challenge
is how to generate models for simulation starting from the structural and behavioural
models.
RC2.2: Automation for timing analysis. The challenge is how to generate the whole
set of meaningful models entailing different allocations.
RC2.3: Automation for back-propagation. The challenge is how to use the observed
values for providing guidance to the engineer for taking evidence-based design deci-
sions.
18 Alessio Bucaioni
3.3 Time Plan
In order to tackle the above mentioned RCs, we divide A-CPS into 6 project phases
(PPs) as follows. PP1: identification and specification of requirements and use cases,
PP2: identification of modelling concepts for high-performance vehicular systems, PP3:
automation for simulation-based assessment of timing, PP4: automation for timing anal-
ysis, PP5: back-propagation and exploitation of observed values and PP6: validation
and dissemination of results. Fig. 1 shows a summary of time plan for the different PPs.
A-CPS starts in April 2019 and ends in March 2021.
Fig. 1: A-CPS time plan for the different PPs
PP1 starts in April 2019 and has a duration of three months. PP2, PP3 and PP4 have
a duration of six months each and start in June 2019, November 2019 and April 2020,
respectively. PP5 starts in September 2020 and has a duration of four months. The
dissemination activities in PP6 are carried out in correspondence of termination of the
previous PPs while the evaluation activities in PP6 start in January 2021 and have a
duration of three months. We are not planning to run more than two technical PPs in
parallel.
3.4 Research Methodology
A-CPS employs a research methodology being an adaptation of the model for tech-
nology transfer described in [7]. The key features of this methodology are a tight col-
laboration between industry and academia and a three-step validation process ensuring
that the research results will have both academic and industrial relevance. The research
methodology starts with the definition of the project research goal and related chal-
lenges. For each challenge, one (or a set of) candidate solution(s) will be identified.
Each solution will be validated from the research leader using use cases. Based on the
results of the first validation step, the candidate solution will be further validated in
dedicated workshops with the industrial experts, first, and on industrial use cases, later.
A-CPS: Automation in High-performance Cyber Physical Systems Development 19
3.5 Expected Outcomes
In A-CPS, we target i) the extensions of existing vehicular-specific modelling lan-
guages, ii) the definition of automatic mechanisms enabling simulation- and analysis-
based assessment of timing as well as back-propagation and exploitation of the observed
results. We plan to disseminate the A-CPS results through 1 journal paper, 3 conference
papers, 1 work-in-progress paper, 1 technical report and 5 case study demonstrators.
A-CPS will provide Dr. Alessio Bucaioni with the opportunity to develop into an inde-
pendent researcher in the area of model-driven engineering for cyber physical systems.
A-CPS will help MDH in enhancing its competences in the domain of model-based en-
gineering of embedded systems thus in strengthening its position as a leading research
environment in such a domain. This project will provide AS with an opportunity to ex-
tend its commercial tools suite by supporting the modelling, analysis and simulation for
parallel heterogeneous platforms (currently missing) to keep up with the pace of cus-
tomers’ technology shifts. A-CPS will provide VGTT with a unique possibility to shape
the future of their current software development solutions by participating directly to
their enhancement for upcoming technology shifts such as autonomous vehicles based
on parallel heterogeneous platforms.
4 State of the Art
In the last decades, a plethora of domain-specific modelling languages and model-based
methodologies have been proposed for the software development of vehicular embed-
ded systems for single-core. EAST-ADL, AUTOSAR and RCM are just some examples,
if we consider the automotive domain. Recently these languages have been provided
with limited support for multicore [10] [4], but they have not been provided with sup-
port for heterogeneous platforms. There are a number of AUTOSAR-based frameworks
for the specification of timing-analysis as [15] [6]. However, because AUTOSAR does
not differentiate between the control and the data flows at the application software level,
these frameworks can not provide precise timing analysis at early stages of the devel-
opment. Moreover, they can not be employed for heterogeneous platforms. Based on
RCM, the work on [12] leverages high-precision timing analysis at system level for ho-
mogeneous platform. However, the approach is fully manual. Given the ubiquity of soft-
ware, there exists a corpus of literature devoted to the design of embedded systems and
posing a special focus to timing requirements. In this respect, several works are based
on the use of general-purpose languages such as UML as alternatives to domain-specific
languages. GASPARD is a UML-based framework for the design of parallel embedded
systems [5]. It prescribes a workflow made-up of subsequent analyses and refinement
steps, from higher to lower abstraction levels. GASPARD does not support heterogene-
ity and focus on complementary non functional properties than timing. In recent years,
several approaches dealing with CPS development by adopting multi-paradigm mod-
elling techniques and leveraging simulation mechanisms to perform early analysis of
systems have been proposed [9] [11]. However, they do not address parallelism nor het-
erogeneity. There are several ongoing Swedish and European research projects comple-
mentary to A-CPS. PreView2 aimed at developing predictable software for multi-core
2
http://www.es.mdh.se/projects/442-PreView
20 Alessio Bucaioni
embedded systems. However, no focus is put on heterogeneous platforms, automation
and combining model-based simulation and timing analysis. DPAC3 aims at providing
dependable platforms for computer-controlled functionality in autonomous systems. It
targets software development and execution of embedded systems, but its main focus is
dependability. Moreover, there is no explicit focus on heterogeneous platforms.
References
1. AUTOSAR Techincal Overview, Version 4.3, The AUTOSAR Consortium, Dec., 2016.
http://autosar.org
2. EAST-ADL Domain Model Specification, Deliverable D4.1.1, 2010.
http://www.atesst.org/home/liblocal/docs/ATESST2 D4.1.1 EAST-ADL2-
Specification 2010-06-02.pdf
3. Bézivin, J.: On the unification power of models. Software & Systems Modeling 4(2), 171–
188 (2005)
4. Bucaioni, A., Addazi, L., Cicchetti, A., Ciccozzi, F., Eramo, R., Mubeen, S., Sjödin, M.:
Moves: a model-driven methodology for vehicular embedded systems. Journal of IEEE Ac-
cess 99, 1–20 (January 2018), http://www.es.mdh.se/publications/4996-
5. Gamatié, A., Le Beux, S., Piel, É., Ben Atitallah, R., Etien, A., Marquet, P., Dekeyser, J.L.:
A model-driven design framework for massively parallel embedded systems. ACM Transac-
tions on Embedded Computing Systems (TECS) 10(4), 39 (2011)
6. Goknil, A., DeAntoni, J., Peraldi-Frati, M.A., Mallet, F.: Tool support for the analysis of
tadl2 timing constraints using timesquare. In: ICECCS’2013-18th International Conference
on Engineering of Complex Computer Systems (2013)
7. Gorschek, T., Garre, P., Larsson, S., Wohlin, C.: A model for technology transfer in practice.
IEEE software 23(6), 88–95 (2006)
8. Hänninen, K., Mäki-Turja, J., Sjödin, M., Lindberg, M., Lundbäck, J., Lundbäck, K.L.: The
Rubus Component Model for Resource Constrained Real-Time Systems. In: 3rd IEEE Inter-
national Symposium on Industrial Embedded Systems (June 2008)
9. Jensen, J.C., Chang, D.H., Lee, E.A.: A model-based design methodology for cyber-physical
systems. In: Wireless Communications and Mobile Computing Conference (IWCMC), 2011
7th International. pp. 1666–1671. IEEE (2011)
10. Moghaddam, A.S.: Performance evaluation and modeling of a multicore autosar system.
Gothenburg, Sweden, Tech. Rep (2013)
11. Mosterman, P.J., Vangheluwe, H.: Computer automated multi-paradigm modeling: An intro-
duction. Simulation 80(9), 433–450 (2004)
12. Mubeen, S., Nolte, T., Sjödin, M., Lundbäck, J., Lundbäck, K.L.: Supporting timing analysis
of vehicular embedded systems through the refinement of timing constraints. Software &
Systems Modeling pp. 1–31 (2017)
13. Rajkumar, R., Lee, I., Sha, L., Stankovic, J.: Cyber-physical systems: the next computing
revolution. In: Design Automation Conference (DAC), 2010 47th ACM/IEEE. pp. 731–736.
IEEE (2010)
14. Sendall, S., Kozaczynski, W.: Model transformation: The heart and soul of model-driven
software development. Software, IEEE 20(5), 42–45 (2003), http://dx.doi.org/10.
1109/MS.2003.1231150
15. Stappert, F., Jonsson, J., Mottok, J., Johansson, R.: A design framework for end-to-end
timing constrained automotive applications. Embedded Real-Time Software and Systems
(ERTS) (2010)
3
http://www.es.mdh.se/projects/414-DPAC