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Information Technology Journal
  Year: 2013 | Volume: 12 | Issue: 12 | Page No.: 2286-2295
DOI: 10.3923/itj.2013.2286.2295
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Efficient Data Gathering based on Linear Regression in Wireless Multivariate Monitoring Sensor Networks

Guofeng Yang, Chunsheng Li and Haotian Yang

Gathering sensed information in an energy efficient manner is an important design challenge in the application of wireless sensor networks. The readings of sensors generally exhibit both spatial and temporal redundancies due to redundant node deployment and spatial and temporal correlations between the sensed data. Therefore, in this paper, the distributed regression theory is used to remove the correlation in wireless multivariate monitoring sensor networks. Sensor nodes need not transmit data to one another or the sink and only communicate the regression model parameters. The proposed algorithm reduces amount of data and energy consumption during the data transmission process, thus prolongs the lifetime of the whole networks. In order to validate the algorithm, simulation is carried out to evaluate the energy consumption and prediction accuracy. The result of simulation shows that the proposed algorithm is very suitable for the compression of multivariate monitoring data.
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  •    An Energy Equilibrium Routing Algorithm Based on Cluster-head Prediction for Wireless Sensor Networks
  •    Synchronous Aggregation Scheduling with Minimal Latency in Multihop SensorNet
  •    A New Approximation to Information Fields in Sensor Nets
How to cite this article:

Guofeng Yang, Chunsheng Li and Haotian Yang, 2013. Efficient Data Gathering based on Linear Regression in Wireless Multivariate Monitoring Sensor Networks. Information Technology Journal, 12: 2286-2295.

DOI: 10.3923/itj.2013.2286.2295






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