Design and management of image processing pipelines within CPS: Acquired experience towards the end of the FitOptiVis ECSEL Project

Carlo Sau; Claudia Rinaldi; Luigi Pomante; Francesca Palumbo; Giacomo Valente; Tiziana Fanni; Marcos Martinez; Frank van der Linden; Twan Basten; Marc Geilen; Geran Peeren; Jiří Kadlec; Pekka Jääskeläinen; Lubomír Bulej; Francisco Barranco; Jukka Saarinen; Tero Säntti; Maria Katiuscia Zedda; Victor Sanchez; Shayan Tabatabaei Nikkhah; Dip Goswami; Guillermo Amat; Lukáš Maršík; Mark van Helvoort; Luis Medina; Zaid Al-Ars; Ad de Beer

doi:10.1016/j.micpro.2021.104350

Design and management of image processing pipelines within CPS: Acquired experience towards the end of the FitOptiVis ECSEL Project

Carlo Sau, Claudia Rinaldi, Luigi Pomante, Francesca Palumbo, Giacomo Valente, Tiziana Fanni, Marcos Martinez, Frank van der Linden, Twan Basten, Marc Geilen, Geran Peeren, Jiří Kadlec, Pekka Jääskeläinen, Lubomír Bulej, Francisco Barranco, Jukka Saarinen, Tero Säntti, Maria Katiuscia Zedda, Victor Sanchez, Shayan Tabatabaei NikkhahDip Goswami, Guillermo Amat, Lukáš Maršík, Mark van Helvoort, Luis Medina, Zaid Al-Ars, Ad de Beer

Tietotekniikka

Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu

5 Sitaatiot (Scopus)

11 Lataukset (Pure)

Abstrakti

Cyber-Physical Systems (CPSs) are dynamic and reactive systems interacting with processes, environment and, sometimes, humans. They are often distributed with sensors and actuators, characterized for being smart, adaptive, predictive and react in real-time. Indeed, image- and video-processing pipelines are a prime source for environmental information for systems allowing them to take better decisions according to what they see. Therefore, in FitOptiVis, we are developing novel methods and tools to integrate complex image- and video-processing pipelines. FitOptiVis aims to deliver a reference architecture for describing and optimizing quality and resource management for imaging and video pipelines in CPSs both at design- and run-time. The architecture is concretized in low-power, high-performance, smart components, and in methods and tools for combined design-time and run-time multi-objective optimization and adaptation within system and environment constraints.

Alkuperäiskieli	Englanti
Artikkeli	104350
Julkaisu	Microprocessors and Microsystems
Vuosikerta	87
DOI - pysyväislinkit	https://doi.org/10.1016/j.micpro.2021.104350
Tila	Julkaistu - 2021
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

This work is part of the FitOptiVis project [1] funded by the ECSEL Joint Undertaking under grant number H2020-ECSEL-2017?2?783,162. Several national funding agencies also contributed to the project funding. A special thanks to all the FitOptiVis consortium partners that contributed to the FitOptiVis project on which this paper is based. It is worth noting some ECSEL projects that have provided background and/or reusable results taken into account in FitOptiVis: MegaM@rt2 [138], AQUAS [138], CASPER [139], AFarCloud [141].

Julkaisufoorumi-taso

Jufo-taso 1

!!ASJC Scopus subject areas

Software
Hardware and Architecture
Computer Networks and Communications
Artificial Intelligence

Pääsy asiakirjaan

10.1016/j.micpro.2021.104350

design_and_management_of_image
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Siteeraa tätä

Sau, C., Rinaldi, C., Pomante, L., Palumbo, F., Valente, G., Fanni, T., Martinez, M., van der Linden, F., Basten, T., Geilen, M., Peeren, G., Kadlec, J., Jääskeläinen, P., Bulej, L., Barranco, F., Saarinen, J., Säntti, T., Zedda, M. K., Sanchez, V., ... de Beer, A. (2021). Design and management of image processing pipelines within CPS: Acquired experience towards the end of the FitOptiVis ECSEL Project. Microprocessors and Microsystems, 87, Artikkeli 104350. https://doi.org/10.1016/j.micpro.2021.104350

@article{b97e731d2e91448389b72d52c9f26e06,

title = "Design and management of image processing pipelines within CPS: Acquired experience towards the end of the FitOptiVis ECSEL Project",

abstract = "Cyber-Physical Systems (CPSs) are dynamic and reactive systems interacting with processes, environment and, sometimes, humans. They are often distributed with sensors and actuators, characterized for being smart, adaptive, predictive and react in real-time. Indeed, image- and video-processing pipelines are a prime source for environmental information for systems allowing them to take better decisions according to what they see. Therefore, in FitOptiVis, we are developing novel methods and tools to integrate complex image- and video-processing pipelines. FitOptiVis aims to deliver a reference architecture for describing and optimizing quality and resource management for imaging and video pipelines in CPSs both at design- and run-time. The architecture is concretized in low-power, high-performance, smart components, and in methods and tools for combined design-time and run-time multi-objective optimization and adaptation within system and environment constraints.",

keywords = "Cyber-physical systems, Distributed system, Heterogeneous system, Image processing, Multi-objective optimization, Video processing",

author = "Carlo Sau and Claudia Rinaldi and Luigi Pomante and Francesca Palumbo and Giacomo Valente and Tiziana Fanni and Marcos Martinez and {van der Linden}, Frank and Twan Basten and Marc Geilen and Geran Peeren and Ji{\v r}{\'i} Kadlec and Pekka J{\"a}{\"a}skel{\"a}inen and Lubom{\'i}r Bulej and Francisco Barranco and Jukka Saarinen and Tero S{\"a}ntti and Zedda, {Maria Katiuscia} and Victor Sanchez and Nikkhah, {Shayan Tabatabaei} and Dip Goswami and Guillermo Amat and Luk{\'a}{\v s} Mar{\v s}{\'i}k and {van Helvoort}, Mark and Luis Medina and Zaid Al-Ars and {de Beer}, Ad",

note = "Funding Information: This work is part of the FitOptiVis project [1] funded by the ECSEL Joint Undertaking under grant number H2020-ECSEL-2017?2?783,162. Several national funding agencies also contributed to the project funding. A special thanks to all the FitOptiVis consortium partners that contributed to the FitOptiVis project on which this paper is based. It is worth noting some ECSEL projects that have provided background and/or reusable results taken into account in FitOptiVis: MegaM@rt2 [138], AQUAS [138], CASPER [139], AFarCloud [141]. Publisher Copyright: {\textcopyright} 2021",

year = "2021",

doi = "10.1016/j.micpro.2021.104350",

language = "English",

volume = "87",

journal = "Microprocessors and Microsystems",

issn = "0141-9331",

publisher = "Elsevier B.V.",

}

Sau, C, Rinaldi, C, Pomante, L, Palumbo, F, Valente, G, Fanni, T, Martinez, M, van der Linden, F, Basten, T, Geilen, M, Peeren, G, Kadlec, J, Jääskeläinen, P, Bulej, L, Barranco, F, Saarinen, J, Säntti, T, Zedda, MK, Sanchez, V, Nikkhah, ST, Goswami, D, Amat, G, Maršík, L, van Helvoort, M, Medina, L, Al-Ars, Z & de Beer, A 2021, 'Design and management of image processing pipelines within CPS: Acquired experience towards the end of the FitOptiVis ECSEL Project', Microprocessors and Microsystems, Vuosikerta 87, 104350. https://doi.org/10.1016/j.micpro.2021.104350

TY - JOUR

T1 - Design and management of image processing pipelines within CPS

T2 - Acquired experience towards the end of the FitOptiVis ECSEL Project

AU - Sau, Carlo

AU - Rinaldi, Claudia

AU - Pomante, Luigi

AU - Palumbo, Francesca

AU - Valente, Giacomo

AU - Fanni, Tiziana

AU - Martinez, Marcos

AU - van der Linden, Frank

AU - Basten, Twan

AU - Geilen, Marc

AU - Peeren, Geran

AU - Kadlec, Jiří

AU - Jääskeläinen, Pekka

AU - Bulej, Lubomír

AU - Barranco, Francisco

AU - Saarinen, Jukka

AU - Säntti, Tero

AU - Zedda, Maria Katiuscia

AU - Sanchez, Victor

AU - Nikkhah, Shayan Tabatabaei

AU - Goswami, Dip

AU - Amat, Guillermo

AU - Maršík, Lukáš

AU - van Helvoort, Mark

AU - Medina, Luis

AU - Al-Ars, Zaid

AU - de Beer, Ad

N1 - Funding Information: This work is part of the FitOptiVis project [1] funded by the ECSEL Joint Undertaking under grant number H2020-ECSEL-2017?2?783,162. Several national funding agencies also contributed to the project funding. A special thanks to all the FitOptiVis consortium partners that contributed to the FitOptiVis project on which this paper is based. It is worth noting some ECSEL projects that have provided background and/or reusable results taken into account in FitOptiVis: MegaM@rt2 [138], AQUAS [138], CASPER [139], AFarCloud [141]. Publisher Copyright: © 2021

PY - 2021

Y1 - 2021

N2 - Cyber-Physical Systems (CPSs) are dynamic and reactive systems interacting with processes, environment and, sometimes, humans. They are often distributed with sensors and actuators, characterized for being smart, adaptive, predictive and react in real-time. Indeed, image- and video-processing pipelines are a prime source for environmental information for systems allowing them to take better decisions according to what they see. Therefore, in FitOptiVis, we are developing novel methods and tools to integrate complex image- and video-processing pipelines. FitOptiVis aims to deliver a reference architecture for describing and optimizing quality and resource management for imaging and video pipelines in CPSs both at design- and run-time. The architecture is concretized in low-power, high-performance, smart components, and in methods and tools for combined design-time and run-time multi-objective optimization and adaptation within system and environment constraints.

AB - Cyber-Physical Systems (CPSs) are dynamic and reactive systems interacting with processes, environment and, sometimes, humans. They are often distributed with sensors and actuators, characterized for being smart, adaptive, predictive and react in real-time. Indeed, image- and video-processing pipelines are a prime source for environmental information for systems allowing them to take better decisions according to what they see. Therefore, in FitOptiVis, we are developing novel methods and tools to integrate complex image- and video-processing pipelines. FitOptiVis aims to deliver a reference architecture for describing and optimizing quality and resource management for imaging and video pipelines in CPSs both at design- and run-time. The architecture is concretized in low-power, high-performance, smart components, and in methods and tools for combined design-time and run-time multi-objective optimization and adaptation within system and environment constraints.

KW - Cyber-physical systems

KW - Distributed system

KW - Heterogeneous system

KW - Image processing

KW - Multi-objective optimization

KW - Video processing

U2 - 10.1016/j.micpro.2021.104350

DO - 10.1016/j.micpro.2021.104350

M3 - Article

AN - SCOPUS:85119051221

SN - 0141-9331

VL - 87

JO - Microprocessors and Microsystems

JF - Microprocessors and Microsystems

M1 - 104350

ER -

Design and management of image processing pipelines within CPS: Acquired experience towards the end of the FitOptiVis ECSEL Project

Abstrakti

Rahoitus

Julkaisufoorumi-taso

!!ASJC Scopus subject areas

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