A quality-aware approach for selecting context information from redundant context sources

José Bringel Filho (1) , Nazim Agoulmine (1)

1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes

Sensor-rich ubiquitous computing systems could face many inconsistent decisions while selecting context data from redundant sources to compose the context, since low-quality sensor data can be selected to accordingly adapt the environment and services based on context changes. These systems need mechanisms to verify the quality of collected sensor data in order to select reliable context information and reduce the probability of making erroneous context-dependent decisions. Quality of Context (QoC) indicators linked to collected context data can be used to deal with this challenge, offering means to improve the decision-making support of context management frameworks. This paper presents a quality-aware approach for selecting reliable context data from redundant context sources based on the QoC indicator probability of correctness. The proposed approach was embedded in the decision-making support of the context fusion layer of our Context Management Framework (CxtMF), which was developed to provide QoC-enriched context information for ubiquitous healthcare systems.

Keywords: Context data; Context dependent; Context information; Context management; Decision making support; Fusion layers; Low qualities; Probability of correctness; Sensor data; Ubiquitous computing systems; Ubiquitous healthcare system

Domains: Computer Science [cs]; Networking and Internet Architecture [cs.NI]

José Bringel Filho, Nazim Agoulmine. A quality-aware approach for selecting context information from redundant context sources. 7th Latin-American Network Operations and Management Symposium (LANOMS 2011), Oct 2011, Quito, Ecuador. (elec. proc), ⟨10.1109/LANOMS.2011.6102264⟩. ⟨hal-00745094⟩