USING SYNCHRONIZED LIGHTWEIGHT STATE OBSERVERS TO MINIMISE WIRELESS SENSOR RESOURCE UTILISATION

David Lowe, Steve Murray, Xiaoying Kong

2009

Abstract

A major trend in the evolution of the Web is the rapidly growing numbers of web-enabled sensors which provide a rich ability to monitor and control our physical environment. The devices are often cheap, lightweight, rapidly deployed and densely interconnected. The current dominant models of Web-based data monitoring are not well-adapted to the operational needs of these devices, particularly in terms of resource utilization. In this paper we describe an approach to the optimization of the resources utilized by these devices based on the use of synchronized state-observers. By embedding state observers with a minimized footprint into both the sensors and the monitoring Web client, we show that it is possible to minimize the utilization of limited sensor resources such as power and bandwidth, and hence to improve the performance and potential applications of these devices.

References

  1. Costa, P., Picco, G. P., & Rossetto, S. (2005). Publishsubscribe on sensor networks: a semi-probabilistic approach.
  2. Delin, K. A. (2002). The Sensor Web: A MacroInstrument for Coordinated Sensing. Sensors, 2(1), 270-285.
  3. Ellis, G. (2002). Observers in Control Systems: A Practical Guide: Academic Press.
  4. Ganesan, D., Ratnasamy, S., Wang, H., & Estrin, D. (2004). Coping with irregular spatio-temporal sampling in sensor networks. SIGCOMM Comput. Commun. Rev., 34(1), 125-130.
  5. Gaynor, M., Moulton, S. L., & Welsh, M. (2004). Integrating Wireless Sensor Networks with the Grid. IEEE INTERNET COMPUTING, 32-39.
  6. Huang, Y., & Garcia-Molina, H. (2004). Publish/Subscribe in a Mobile Environment. Wireless Networks, 10(6), 643-652.
  7. Ishwar, P., Kumar, A., & Ramchandran, K. (2003). Distributed Sampling for Dense Sensor Networks: A" Bit-Conservation Principle".
  8. Krishnamachari, B., Estrin, D., & Wicker, S. (2002). Modelling Data-Centric Routing in Wireless Sensor Networks.
  9. Li, H., & Fang, J. (2007). Distributed Adaptive Quantization and Estimation for Wireless Sensor Networks. Signal Processing Letters, IEEE, 14(10), 669-672.
  10. Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. Paper presented at the 2nd international conference on Embedded networked sensor systems.
  11. The Zigbee Alliance. (2008). Retrieved 22-Oct, 2008, from http://www.zigbee.org/en/index.asp.
Download


Paper Citation


in Harvard Style

Lowe D., Murray S. and Kong X. (2009). USING SYNCHRONIZED LIGHTWEIGHT STATE OBSERVERS TO MINIMISE WIRELESS SENSOR RESOURCE UTILISATION . In Proceedings of the International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2009) ISBN 978-989-674-008-5, pages 5-12. DOI: 10.5220/0002187300050012


in Bibtex Style

@conference{winsys09,
author={David Lowe and Steve Murray and Xiaoying Kong},
title={USING SYNCHRONIZED LIGHTWEIGHT STATE OBSERVERS TO MINIMISE WIRELESS SENSOR RESOURCE UTILISATION},
booktitle={Proceedings of the International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2009)},
year={2009},
pages={5-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002187300050012},
isbn={978-989-674-008-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2009)
TI - USING SYNCHRONIZED LIGHTWEIGHT STATE OBSERVERS TO MINIMISE WIRELESS SENSOR RESOURCE UTILISATION
SN - 978-989-674-008-5
AU - Lowe D.
AU - Murray S.
AU - Kong X.
PY - 2009
SP - 5
EP - 12
DO - 10.5220/0002187300050012