CMOS: Efficient Clustered Data Monitoring in Sensor Networks

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 repla...

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Main Author: Jun-Ki Min
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2013/704957
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author Jun-Ki Min
author_facet Jun-Ki Min
author_sort Jun-Ki Min
collection DOAJ
description 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.
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series The Scientific World Journal
spelling doaj-art-64a93155162b4330be4de3d865fde1222025-02-03T01:31:23ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/704957704957CMOS: Efficient Clustered Data Monitoring in Sensor NetworksJun-Ki Min0School of Computer Science and Engineering, Korea University of Technology and Education, Byeongcheon-myeon, Cheonan, Chungnam 330-708, Republic of KoreaTiny 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.http://dx.doi.org/10.1155/2013/704957
spellingShingle Jun-Ki Min
CMOS: Efficient Clustered Data Monitoring in Sensor Networks
The Scientific World Journal
title CMOS: Efficient Clustered Data Monitoring in Sensor Networks
title_full CMOS: Efficient Clustered Data Monitoring in Sensor Networks
title_fullStr CMOS: Efficient Clustered Data Monitoring in Sensor Networks
title_full_unstemmed CMOS: Efficient Clustered Data Monitoring in Sensor Networks
title_short CMOS: Efficient Clustered Data Monitoring in Sensor Networks
title_sort cmos efficient clustered data monitoring in sensor networks
url http://dx.doi.org/10.1155/2013/704957
work_keys_str_mv AT junkimin cmosefficientclustereddatamonitoringinsensornetworks