Quality-aware scheduling metrics for adaptive sensor networks

Quality of service in sensor networks is a difficult problem due to unpredictable environment noise, unreliable network communication and varying requirements for wide varieties of applications. In this paper, we present fundamental quality of information metrics using signal-to-noise ratio. These metrics address information quality under varying sensing environments, noise and network bandwidth, and are completely application independent. We use these metrics to develop a quality-aware scheduling system (QSS) which exploits cross-layer control of sensors to effectively schedule data sensing and forwarding. Particularly, we develop and evaluate several QSS scheduling mechanisms: passive, reactive and perceptive. These mechanisms can adapt to environment noise and bandwidth variation by dynamically changing sensor rates. Our results indicate that our QSS is a novel and effective approach to improve the QoS for sensor networks.