A task execution scheme for dew computing with state-of-the-art smartphones

Autores
Hirsch Jofré, Matías Eberardo; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Majchrzak, Tim A.; Grønli, Tor-Morten; Kaindl, Hermann
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The computing resources of today’s smartphones are underutilized most of the time. Using these resources could be highly beneficial in edge computing and fog computing contexts, for example, to support urban services for citizens. However, new challenges, especially regarding job scheduling, arise. Smartphones may form ad hoc networks, but individual devices highly differ in computational capabilities and (tolerable) energy usage. We take into account these particularities to validate a task execution scheme that relies on the computing power that clusters of mobile devices could provide. In this paper, we expand the study of several practical heuristics for job scheduling including execution scenarios with state-of-the-art smartphones. With the results of new simulated scenarios, we confirm previous findings and better comprehend the baseline approaches already proposed for the problem. This study also sheds some light on the capabilities of small-sized clusters comprising mid-range and low-end smartphones when the objective is to achieve real-time stream processing using Tensorflow object recognition models as edge jobs. Ultimately, we strive for industry applications to improve task scheduling for dew computing contexts. Heuristics such as ours plus supporting dew middleware could improve citizen participation by allowing a much wider use of dew computing resources, especially in urban contexts in order to help build smart cities.
Fil: Hirsch Jofré, Matías Eberardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Majchrzak, Tim A.. University Of Agder; Noruega
Fil: Grønli, Tor-Morten. Kristiania University College; Noruega
Fil: Kaindl, Hermann. Technischen Universität Wien; Austria
Materia
DEW COMPUTING
EDGE COMPUTING
JOB SCHEDULING
SCHEDULING HEURISTICS
SMARTPHONE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/174018
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A task execution scheme for dew computing with state-of-the-art smartphonesHirsch Jofré, Matías EberardoMateos Diaz, Cristian MaximilianoZunino Suarez, Alejandro OctavioMajchrzak, Tim A.Grønli, Tor-MortenKaindl, HermannDEW COMPUTINGEDGE COMPUTINGJOB SCHEDULINGSCHEDULING HEURISTICSSMARTPHONEhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The computing resources of today’s smartphones are underutilized most of the time. Using these resources could be highly beneficial in edge computing and fog computing contexts, for example, to support urban services for citizens. However, new challenges, especially regarding job scheduling, arise. Smartphones may form ad hoc networks, but individual devices highly differ in computational capabilities and (tolerable) energy usage. We take into account these particularities to validate a task execution scheme that relies on the computing power that clusters of mobile devices could provide. In this paper, we expand the study of several practical heuristics for job scheduling including execution scenarios with state-of-the-art smartphones. With the results of new simulated scenarios, we confirm previous findings and better comprehend the baseline approaches already proposed for the problem. This study also sheds some light on the capabilities of small-sized clusters comprising mid-range and low-end smartphones when the objective is to achieve real-time stream processing using Tensorflow object recognition models as edge jobs. Ultimately, we strive for industry applications to improve task scheduling for dew computing contexts. Heuristics such as ours plus supporting dew middleware could improve citizen participation by allowing a much wider use of dew computing resources, especially in urban contexts in order to help build smart cities.Fil: Hirsch Jofré, Matías Eberardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Majchrzak, Tim A.. University Of Agder; NoruegaFil: Grønli, Tor-Morten. Kristiania University College; NoruegaFil: Kaindl, Hermann. Technischen Universität Wien; AustriaMultidisciplinary Digital Publishing Institute2021-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/174018Hirsch Jofré, Matías Eberardo; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Majchrzak, Tim A.; Grønli, Tor-Morten; et al.; A task execution scheme for dew computing with state-of-the-art smartphones; Multidisciplinary Digital Publishing Institute; Electronics (Switzerland); 10; 16; 8-2021; 1-222079-9292CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2079-9292/10/16/2006info:eu-repo/semantics/altIdentifier/doi/10.3390/electronics10162006info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:07:19Zoai:ri.conicet.gov.ar:11336/174018instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:07:20.25CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A task execution scheme for dew computing with state-of-the-art smartphones
title A task execution scheme for dew computing with state-of-the-art smartphones
spellingShingle A task execution scheme for dew computing with state-of-the-art smartphones
Hirsch Jofré, Matías Eberardo
DEW COMPUTING
EDGE COMPUTING
JOB SCHEDULING
SCHEDULING HEURISTICS
SMARTPHONE
title_short A task execution scheme for dew computing with state-of-the-art smartphones
title_full A task execution scheme for dew computing with state-of-the-art smartphones
title_fullStr A task execution scheme for dew computing with state-of-the-art smartphones
title_full_unstemmed A task execution scheme for dew computing with state-of-the-art smartphones
title_sort A task execution scheme for dew computing with state-of-the-art smartphones
dc.creator.none.fl_str_mv Hirsch Jofré, Matías Eberardo
Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
Majchrzak, Tim A.
Grønli, Tor-Morten
Kaindl, Hermann
author Hirsch Jofré, Matías Eberardo
author_facet Hirsch Jofré, Matías Eberardo
Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
Majchrzak, Tim A.
Grønli, Tor-Morten
Kaindl, Hermann
author_role author
author2 Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
Majchrzak, Tim A.
Grønli, Tor-Morten
Kaindl, Hermann
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv DEW COMPUTING
EDGE COMPUTING
JOB SCHEDULING
SCHEDULING HEURISTICS
SMARTPHONE
topic DEW COMPUTING
EDGE COMPUTING
JOB SCHEDULING
SCHEDULING HEURISTICS
SMARTPHONE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The computing resources of today’s smartphones are underutilized most of the time. Using these resources could be highly beneficial in edge computing and fog computing contexts, for example, to support urban services for citizens. However, new challenges, especially regarding job scheduling, arise. Smartphones may form ad hoc networks, but individual devices highly differ in computational capabilities and (tolerable) energy usage. We take into account these particularities to validate a task execution scheme that relies on the computing power that clusters of mobile devices could provide. In this paper, we expand the study of several practical heuristics for job scheduling including execution scenarios with state-of-the-art smartphones. With the results of new simulated scenarios, we confirm previous findings and better comprehend the baseline approaches already proposed for the problem. This study also sheds some light on the capabilities of small-sized clusters comprising mid-range and low-end smartphones when the objective is to achieve real-time stream processing using Tensorflow object recognition models as edge jobs. Ultimately, we strive for industry applications to improve task scheduling for dew computing contexts. Heuristics such as ours plus supporting dew middleware could improve citizen participation by allowing a much wider use of dew computing resources, especially in urban contexts in order to help build smart cities.
Fil: Hirsch Jofré, Matías Eberardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Majchrzak, Tim A.. University Of Agder; Noruega
Fil: Grønli, Tor-Morten. Kristiania University College; Noruega
Fil: Kaindl, Hermann. Technischen Universität Wien; Austria
description The computing resources of today’s smartphones are underutilized most of the time. Using these resources could be highly beneficial in edge computing and fog computing contexts, for example, to support urban services for citizens. However, new challenges, especially regarding job scheduling, arise. Smartphones may form ad hoc networks, but individual devices highly differ in computational capabilities and (tolerable) energy usage. We take into account these particularities to validate a task execution scheme that relies on the computing power that clusters of mobile devices could provide. In this paper, we expand the study of several practical heuristics for job scheduling including execution scenarios with state-of-the-art smartphones. With the results of new simulated scenarios, we confirm previous findings and better comprehend the baseline approaches already proposed for the problem. This study also sheds some light on the capabilities of small-sized clusters comprising mid-range and low-end smartphones when the objective is to achieve real-time stream processing using Tensorflow object recognition models as edge jobs. Ultimately, we strive for industry applications to improve task scheduling for dew computing contexts. Heuristics such as ours plus supporting dew middleware could improve citizen participation by allowing a much wider use of dew computing resources, especially in urban contexts in order to help build smart cities.
publishDate 2021
dc.date.none.fl_str_mv 2021-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/174018
Hirsch Jofré, Matías Eberardo; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Majchrzak, Tim A.; Grønli, Tor-Morten; et al.; A task execution scheme for dew computing with state-of-the-art smartphones; Multidisciplinary Digital Publishing Institute; Electronics (Switzerland); 10; 16; 8-2021; 1-22
2079-9292
CONICET Digital
CONICET
url http://hdl.handle.net/11336/174018
identifier_str_mv Hirsch Jofré, Matías Eberardo; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Majchrzak, Tim A.; Grønli, Tor-Morten; et al.; A task execution scheme for dew computing with state-of-the-art smartphones; Multidisciplinary Digital Publishing Institute; Electronics (Switzerland); 10; 16; 8-2021; 1-22
2079-9292
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2079-9292/10/16/2006
info:eu-repo/semantics/altIdentifier/doi/10.3390/electronics10162006
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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