Measuring the quality of information in clustering protocols for sensor networks

The performance of a clustering protocol for sensor network is often measured by the energy spent by the network. But there are other metrics that are of significance, namely the latency of the network and the quality of the overall information sensed by the network. In this paper, we have show three ways to measure the quality of information obtained in a sensor network. Our first method an information loss metric that we have formulated is a statistical method to estimate the quality of information. Our second metric, the entropy ratio metric based on Shannon's information theory gives us a ratio that indicates the quality of information obtained. Our third method is based on variance. This deterministic method essentially calculates the mean square error between the true and the estimated signal over all the nodes. This simple method provides an effective way to measure the amount of information lost.

[1]  Chen-Khong Tham,et al.  Data loss regulation to ensure information quality in sensor networks , 2005, 2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[2]  Jie Wu,et al.  EECS: an energy efficient clustering scheme in wireless sensor networks , 2005, PCCC 2005. 24th IEEE International Performance, Computing, and Communications Conference, 2005..

[3]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[4]  Stephen B. Vardeman,et al.  Statistics for Engineering Problem Solving. , 1996 .

[5]  Melody Moh,et al.  On data aggregation quality and energy efficiency of wireless sensor network protocols - extended summary , 2004, First International Conference on Broadband Networks.

[6]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[7]  D.P. Agrawal,et al.  APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless , 2002, Proceedings 16th International Parallel and Distributed Processing Symposium.

[8]  Richard M. Brugger Statistics for Engineering Problem Solving , 1993 .

[9]  A. Manjeshwar,et al.  TEEN: a routing protocol for enhanced efficiency in wireless sensor networks , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.