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The Scientific World Journal
Volume 2013, Article ID 704957, 11 pages
Research Article

CMOS: Efficient Clustered Data Monitoring in Sensor Networks

School of Computer Science and Engineering, Korea University of Technology and Education, Byeongcheon-myeon, Cheonan, Chungnam 330-708, Republic of Korea

Received 5 August 2013; Accepted 2 October 2013

Academic Editors: J. Moreno and Y. Wang

Copyright © 2013 Jun-Ki Min. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Tiny and smart sensors enable applications that access a network of hundreds or thousands of sensors. Thus, recently, many researchers have paid attention to wireless sensor networks (WSNs). The limitation of energy is critical since most sensors are battery-powered and it is very difficult to replace batteries in cases that sensor networks are utilized outdoors. Data transmission between sensor nodes needs more energy than computation in a sensor node. In order to reduce the energy consumption of sensors, we present an approximate data gathering technique, called CMOS, based on the Kalman filter. The goal of CMOS is to efficiently obtain the sensor readings within a certain error bound. In our approach, spatially close sensors are grouped as a cluster. Since a cluster header generates approximate readings of member nodes, a user query can be answered efficiently using the cluster headers. In addition, we suggest an energy efficient clustering method to distribute the energy consumption of cluster headers. Our simulation results with synthetic data demonstrate the efficiency and accuracy of our proposed technique.