Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis

Abstract: Human Centered Computing is a novel paradigm to process context information of human being's environment in which computers are invisible to the subject, providing tools and services depending on the context of each individual. An increasing interest is growing regarding embedded comp...

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Autores:
Tipo de recurso:
Fecha de publicación:
2014
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
eng
OAI Identifier:
oai:repository.udem.edu.co:11407/2307
Acceso en línea:
http://hdl.handle.net/11407/2307
Palabra clave:
Hardware Platforms
HCC
Non Functional Requirements
Optimization
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restrictedAccess
License
http://purl.org/coar/access_right/c_16ec
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repository_id_str
spelling 2016-06-23T21:52:06Z2016-06-23T21:52:06Z2014978989984343121660727http://hdl.handle.net/11407/230710.1109/CISTI.2014.6876901Abstract: Human Centered Computing is a novel paradigm to process context information of human being's environment in which computers are invisible to the subject, providing tools and services depending on the context of each individual. An increasing interest is growing regarding embedded computers since they offer advantages related to portability, dedicated tasks, invisibility, amongst others. However, a plenty of hardware platforms are in the market, so it is complicated to determine which the best for a particular need. Benchmarks make those tasks easier by performing measurements in hardware by running applications and performing comparisons. Nevertheless, they are thought to meet some quite particular kinds of applications. Moreover, if some benchmark applications have to be merged, i.e. voice or images processing, there are not schemes to correctly measure hardware platforms. On the other hand, requirements such as reliability and availability are not commonly assessed as a dependant set in hardware platforms. In this work, we propose a novel method to select hardware architectures for Human Centered Computing based on benchmarking, genetic algorithms, weighted sums and statistical distances in order to consider non-functional requirements.engIEEE Computer Societyhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6876901Iberian Conference on Information Systems and Technologies, CISTI 2014, Article number 6876901ScopusMethod to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysisConference Paperinfo:eu-repo/semantics/conferenceObjecthttp://purl.org/coar/resource_type/c_c94finfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/access_right/c_16ecTelecommunications Engineering Department, University of Medellin, Medellin, ColombiaSystem Engineering Department, University of Medellin, Medellin, ColombiaCommercialization Department, UNE Telecommunications, Medellin, ColombiaSoftware Engineering Department, University of Antioquia, Medellin, ColombiaGonzález M.González L.Echeverri J.Aristizábal M.Urrego G.Pérez A.L.Hardware PlatformsHCCNon Functional RequirementsOptimization11407/2307oai:repository.udem.edu.co:11407/23072020-05-27 16:33:19.184Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co
dc.title.spa.fl_str_mv Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
title Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
spellingShingle Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
Hardware Platforms
HCC
Non Functional Requirements
Optimization
title_short Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
title_full Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
title_fullStr Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
title_full_unstemmed Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
title_sort Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis
dc.contributor.affiliation.spa.fl_str_mv Telecommunications Engineering Department, University of Medellin, Medellin, Colombia
System Engineering Department, University of Medellin, Medellin, Colombia
Commercialization Department, UNE Telecommunications, Medellin, Colombia
Software Engineering Department, University of Antioquia, Medellin, Colombia
dc.subject.keyword.eng.fl_str_mv Hardware Platforms
HCC
Non Functional Requirements
Optimization
topic Hardware Platforms
HCC
Non Functional Requirements
Optimization
description Abstract: Human Centered Computing is a novel paradigm to process context information of human being's environment in which computers are invisible to the subject, providing tools and services depending on the context of each individual. An increasing interest is growing regarding embedded computers since they offer advantages related to portability, dedicated tasks, invisibility, amongst others. However, a plenty of hardware platforms are in the market, so it is complicated to determine which the best for a particular need. Benchmarks make those tasks easier by performing measurements in hardware by running applications and performing comparisons. Nevertheless, they are thought to meet some quite particular kinds of applications. Moreover, if some benchmark applications have to be merged, i.e. voice or images processing, there are not schemes to correctly measure hardware platforms. On the other hand, requirements such as reliability and availability are not commonly assessed as a dependant set in hardware platforms. In this work, we propose a novel method to select hardware architectures for Human Centered Computing based on benchmarking, genetic algorithms, weighted sums and statistical distances in order to consider non-functional requirements.
publishDate 2014
dc.date.created.none.fl_str_mv 2014
dc.date.accessioned.none.fl_str_mv 2016-06-23T21:52:06Z
dc.date.available.none.fl_str_mv 2016-06-23T21:52:06Z
dc.type.eng.fl_str_mv Conference Paper
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_c94f
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/conferenceObject
dc.identifier.isbn.none.fl_str_mv 9789899843431
dc.identifier.issn.none.fl_str_mv 21660727
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/11407/2307
dc.identifier.doi.none.fl_str_mv 10.1109/CISTI.2014.6876901
identifier_str_mv 9789899843431
21660727
10.1109/CISTI.2014.6876901
url http://hdl.handle.net/11407/2307
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.isversionof.spa.fl_str_mv http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6876901
dc.relation.ispartofen.eng.fl_str_mv Iberian Conference on Information Systems and Technologies, CISTI 2014, Article number 6876901
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.accessrights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
rights_invalid_str_mv http://purl.org/coar/access_right/c_16ec
dc.publisher.spa.fl_str_mv IEEE Computer Society
dc.source.spa.fl_str_mv Scopus
institution Universidad de Medellín
repository.name.fl_str_mv Repositorio Institucional Universidad de Medellin
repository.mail.fl_str_mv repositorio@udem.edu.co
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