Publicação
Lightweight multivariate sensing in WSNs
| Resumo: | This paper proposes a self-adaptive sampling scheme for WSNs, which aims at capturing accurately the behavior of the physical parameters of interest in each specific WSN context yet reducing the overhead in terms of sensing events. The sampling scheme relies on a set of low-complexity rules capable of auto-regulate the sensing frequency in accordance with each parameter behavior. As proof-of-concept, based on real environmental datasets, we provide statistical indicators illustrating the added value of the proposed sampling scheme in reducing sensing events without compromising the estimation accuracy of physical phenomena. |
|---|---|
| Autores principais: | Silva, Joao Marco C. |
| Outros Autores: | Carvalho, Paulo; Bispo, Kalil Araujo; Lima, Solange |
| Assunto: | Sampling techniques Data sensing Network measurements WSNs |
| Ano: | 2016 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | This paper proposes a self-adaptive sampling scheme for WSNs, which aims at capturing accurately the behavior of the physical parameters of interest in each specific WSN context yet reducing the overhead in terms of sensing events. The sampling scheme relies on a set of low-complexity rules capable of auto-regulate the sensing frequency in accordance with each parameter behavior. As proof-of-concept, based on real environmental datasets, we provide statistical indicators illustrating the added value of the proposed sampling scheme in reducing sensing events without compromising the estimation accuracy of physical phenomena. |
|---|
Atividades financiadas
Não foram encontrados projetos financiados.