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Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks

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Detalhes bibliográficos
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.
Autores principais:Abreu, Carlos
Outros Autores:Miranda, Francisco; Mendes, Paulo M.
Assunto:Quality of service Adaptive Context-aware Biomedical wireless sensor networks
Ano:2016
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade de Aveiro
Idioma:inglês
Origem:RIA - Repositório Institucional da Universidade de Aveiro
Descrição
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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