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...
- 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
- Rights
- restrictedAccess
- License
- http://purl.org/coar/access_right/c_16ec
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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 |
_version_ |
1814159150352957440 |