Quality-aware scheduling metrics for adaptive sensor networks

  • Authors:

  • Vespa, Lucas Vespa;Weng, Ning Weng

  • Affiliations:

  • Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL, USA;Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL, USA

  • Venue:
  • LCN '10 Proceedings of the 2010 IEEE 35th Conference on Local Computer Networks
  • Year:
  • 2010

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Abstract

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.