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Data aggregation of Moving Object with Dynamic Clustering in Wireless Sensor Network

In Wireless Sensor networks due to unfavorable environmental conditions that sensor nodes are placed into and some other reasons, power consumption of sensor node is the main constrained. Emerging in-network aggregation techniques are increasingly being sought to overcome this key challenge and to save precious energy. One application of WSN is in data gathering of moving object. In order to achieve complete coverage, this type of application require spatially dense sensor deployment, which under close observation, exhibit important spatial correlation characteristics. Rate distortion (RD) theory is data aggregation technique that can take advantage of this type of correlation to reduce network load with the help of cluster based communication model. In this paper we introduce a more realistic spatial correlation analysis that makes the RD theory based aggregation model to be more efficient.