Using QoC for improving energy-efficient context management in U-Health Systems

Abstract

Context Management Framework (CMF) for Ubiquitous Health (U-Health) Systems should be able to continuously gather raw data from observed entities to characterize their current situation (context). However, the death of battery-dependent sensors reduce their ability for detecting the context, which directly affects the availability of context-aware u-health services. This paper proposes the use of Quality of Context (QoC) integrated with a data reduction approach to minimize the amount of sensed raw data sent to CMF, reducing the energy consumption and maximizing the lifetime of sensor-based CMF. The proposed approach rebuilds the gathered raw data taking into account QoC requirements, avoiding the loss of precision (QoC Indicator precision) and timeliness (QoC Indicator up-to-dateness), which has been integrated into our Context Management Framework (CxtMF). Experimental results demonstrate the effectiveness of our approach by reducing the amount of packets sent over network to 3% for the ECG monitoring service.