Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/16468 |
Resumo: | The use of wireless sensor networks in healthcare has the potential to enhance the services provided to citizens. In particular they play an important role in the development of state-of-the-art patient monitoring applications. Nevertheless due to the critical nature of the data conveyed by such patient monitoring applications they have to fulfil high standards of quality of service in order to obtain the confidence of all players in the healthcare industry. In such context vis-à-vis the quality of service being provided by the wireless sensor network this work presents an adaptive and context-aware method to detect and classify performance degradation events. The proposed method has the ability to catch the most significant and damaging variations on the metrics being used to quantify the quality of service provided by the network without overreacting to small and innocuous variations on the metric’s value. |
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Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networksQuality of serviceAdaptiveContext-awareBiomedical wireless sensor networksThe use of wireless sensor networks in healthcare has the potential to enhance the services provided to citizens. In particular they play an important role in the development of state-of-the-art patient monitoring applications. Nevertheless due to the critical nature of the data conveyed by such patient monitoring applications they have to fulfil high standards of quality of service in order to obtain the confidence of all players in the healthcare industry. In such context vis-à-vis the quality of service being provided by the wireless sensor network this work presents an adaptive and context-aware method to detect and classify performance degradation events. The proposed method has the ability to catch the most significant and damaging variations on the metrics being used to quantify the quality of service provided by the network without overreacting to small and innocuous variations on the metric’s value.AIP Publishing2018-07-20T14:00:57Z2016-01-01T00:00:00Z20162016-12-31T12:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/16468eng0094-243X10.1063/1.4952157Abreu, CarlosMiranda, FranciscoMendes, Paulo M.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T11:30:15Zoai:ria.ua.pt:10773/16468Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:51:24.968317Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks |
title |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks |
spellingShingle |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks Abreu, Carlos Quality of service Adaptive Context-aware Biomedical wireless sensor networks |
title_short |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks |
title_full |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks |
title_fullStr |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks |
title_full_unstemmed |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks |
title_sort |
Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks |
author |
Abreu, Carlos |
author_facet |
Abreu, Carlos Miranda, Francisco Mendes, Paulo M. |
author_role |
author |
author2 |
Miranda, Francisco Mendes, Paulo M. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Abreu, Carlos Miranda, Francisco Mendes, Paulo M. |
dc.subject.por.fl_str_mv |
Quality of service Adaptive Context-aware Biomedical wireless sensor networks |
topic |
Quality of service Adaptive Context-aware Biomedical wireless sensor networks |
description |
The use of wireless sensor networks in healthcare has the potential to enhance the services provided to citizens. In particular they play an important role in the development of state-of-the-art patient monitoring applications. Nevertheless due to the critical nature of the data conveyed by such patient monitoring applications they have to fulfil high standards of quality of service in order to obtain the confidence of all players in the healthcare industry. In such context vis-à-vis the quality of service being provided by the wireless sensor network this work presents an adaptive and context-aware method to detect and classify performance degradation events. The proposed method has the ability to catch the most significant and damaging variations on the metrics being used to quantify the quality of service provided by the network without overreacting to small and innocuous variations on the metric’s value. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01T00:00:00Z 2016 2016-12-31T12:00:00Z 2018-07-20T14:00:57Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/16468 |
url |
http://hdl.handle.net/10773/16468 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0094-243X 10.1063/1.4952157 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
AIP Publishing |
publisher.none.fl_str_mv |
AIP Publishing |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137563721596928 |