research-article

Mapping functional behavior onto architectural model in a model driven embedded system design

Authors:

Sandeep K. Shukla,

Jean Pierre Talpin Inria,

Huafeng YuAuthors Info & Claims

SAC '15: Proceedings of the 30th Annual ACM Symposium on Applied Computing

Pages 1624 - 1630

https://doi.org/10.1145/2695664.2695934

Published: 13 April 2015 Publication History

Abstract

The ever-increasing complexity in embedded systems especially in the automobile industry in the recent years has necessitated model-driven engineering. In this paper, we consider the problem of mapping functional behavior onto an architectural model captured in AADL in order to optimize end-to-end delay in executing a distributed function on the specified platform architecture. Our work presupposes that an architectural platform model is fixed due to existing hardware platform that the designers have to work with, whereas a specific functional feature is being designed in software, and implemented on the given platform. We therefore, consider the problem as a behavior modeling followed by mapping of behavioral components including computation, and communication. This mapping requires both spatial mapping as well as temporal mapping. Spatial mapping means binding of computational nodes in the behavioral model to processors/controllers etc., communications to the platform bus; and the temporal binding is done by scheduling the computation on the platform. We explain our method by way of a case study of an adaptive cruise control(ACC) system whose behavior model is represented with a data-flow graph(DFG) captured in LUSTRE. A static schedule is derived from the DFG and then mapped to the platform architecture model by formulating a non-linear optimization problem. The resulting problem being at least NP-hard, we propose use of simulated annealing or other heuristic algorithms to solve the optimization problem. The limitations of our method are discussed as well.

References

[1]

Anderson, Matthew, and Sandeep K. Shukla. "APECS: An AADL and polychrony based embedded computing system design environment with an elevator control case study."MEMOCODE, 2013 Eleventh IEEE/ACM International Conference on IEEE, 2013.

[2]

Dennis, Jack Bonnell. "Data flow supercomputers." Computer 13.11 (1980): 48--56.

Digital Library

[3]

Babb, Robert G. "Parallel processing with large-grain data flow techniques." Computer 17.7 (1984): 55--61.

Digital Library

[4]

Pilaud, Daniel, N. Halbwachs, and J. A. Plaice. "LUSTRE: A declarative language for programming synchronous systems." Proceedings of the 14th Annual ACM Symposium on Principles of Programming Languages (14th POPL 1987). ACM, New York, NY. Vol. 178. 1987.

Digital Library

[5]

Pinello, Claudio, Luca P. Carloni, and Alberto L. Sangiovanni-Vincentelli. "Fault-tolerant deployment of embedded software for cost-sensitive real-time feedback-control applications." Proceedings of the conference on Design, automation and test in Europe-Volume 2. IEEE Computer Society, 2004.

Digital Library

[6]

Sangiovanni-Vincentelli, Alberto, and Marco Di Natale. "Embedded system design for automotive applications." IEEE Computer 40.10 (2007): 42--51.

Digital Library

[7]

Sangiovanni-Vincentelli, Alberto, and Grant Martin. "Platform-based design and software design methodology for embedded systems." IEEE Design & Test of Computers 18.6 (2001): 23--33.

Digital Library

[8]

Zheng, Wei, et al. "Synthesis of task and message activation models in real-time distributed automotive systems." Proceedings of the conference on Design, automation and test in Europe. EDA Consortium, 2007.

Digital Library

[9]

Davare, Abhijit, et al. "Period optimization for hard real-time distributed automotive systems." Proceedings of the 44th annual Design Automation Conference. ACM, 2007.

Digital Library

[10]

Racu, Razvan, Marek Jersak, and Rolf Ernst. "Applying sensitivity analysis in real-time distributed systems." Real Time and Embedded Technology and Applications Symposium, 2005. RTAS 2005. 11th IEEE. IEEE, 2005.

Digital Library

[11]

Vulgarakis, Aneta, et al. "Integrating behavioral descriptions into a component model for embedded systems." Software Engineering and Advanced Applications (SEAA), 2010 36th EUROMICRO Conference on. IEEE, 2010.

Digital Library

[12]

Basu, Ananda, Marius Bozga, and Joseph Sifakis. "Modeling heterogeneous real-time components in BIP." Software Engineering and Formal Methods, 2006. SEFM 2006. Fourth IEEE International Conference on. Ieee, 2006.

Digital Library

[13]

Orsila, Heikki. "Optimizing algorithms for task graph mapping on multiprocessor system on chip." Tampereen teknillinen yliopisto. Julkaisu-Tampere University of Technology. Publication; 972 (2011).

[14]

Braun, Tracy D., et al. "A comparison study of static mapping heuristics for a class of meta-tasks on heterogeneous computing systems." Heterogeneous Computing Workshop, 1999.(HCW'99) Proceedings. Eighth. IEEE, 1999.

Digital Library

[15]

Brooks, S. P., and B. J. T. Morgan. "Optimization using simulated annealing." The Statistician (1995): 241--257.

[16]

Konak, Abdullah, David W. Coit, and Alice E. Smith. "Multi-objective optimization using genetic algorithms: A tutorial." Reliability Engineering & System Safety 91.9 (2006): 992--1007.

[17]

Beaty, Steven J. "Genetic algorithms versus tabu search for instruction scheduling." Artificial Neural Nets and Genetic Algorithms. Springer Vienna, 1993.

[18]

The University of York, n.d. Web. 6 Oct. 2014. <http://www.cs.york.ac.uk/rts/books/CRTJbook/Lecture19.ppt> <http://www.cs.york.ac.uk/rts/books/CRTJbook/Lecture13.ppt>

Cited By

Rizzon LPasserone R(2016)Cyber/physical co-design in practice: Case studies in metroII2016 11th IEEE Symposium on Industrial Embedded Systems (SIES)10.1109/SIES.2016.7509408(1-10)Online publication date: May-2016
https://doi.org/10.1109/SIES.2016.7509408
Yu HJoshi PTalpin JShukla SShiraishi S(2015)The challenge of interoperabilityProceedings of the 52nd Annual Design Automation Conference10.1145/2744769.2747945(1-6)Online publication date: 7-Jun-2015
https://dl.acm.org/doi/10.1145/2744769.2747945

Index Terms

Mapping functional behavior onto architectural model in a model driven embedded system design
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software architectures

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cover image ACM Conferences

SAC '15: Proceedings of the 30th Annual ACM Symposium on Applied Computing

April 2015

2418 pages

ISBN:9781450331968

DOI:10.1145/2695664

Conference Chairs:
Roger L. Wainwright
University of Tulsa
,
Juan Manuel Corchado
University of Salamanca, Spain
,
Program Chairs:
Alessio Bechini
University of Pisa, Italy
,
Jiman Hong
Soongsil University, South Korea

Copyright © 2015 ACM.

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New York, NY, United States

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Published: 13 April 2015

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SAC 2015: Symposium on Applied Computing

April 13 - 17, 2015

Salamanca, Spain

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SAC '15 Paper Acceptance Rate 291 of 1,211 submissions, 24%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Rizzon LPasserone R(2016)Cyber/physical co-design in practice: Case studies in metroII2016 11th IEEE Symposium on Industrial Embedded Systems (SIES)10.1109/SIES.2016.7509408(1-10)Online publication date: May-2016
https://doi.org/10.1109/SIES.2016.7509408
Yu HJoshi PTalpin JShukla SShiraishi S(2015)The challenge of interoperabilityProceedings of the 52nd Annual Design Automation Conference10.1145/2744769.2747945(1-6)Online publication date: 7-Jun-2015
https://dl.acm.org/doi/10.1145/2744769.2747945

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