A Spatial Correlation Analysis for Moving Object Data Aggregation in WSNs

In Wireless Sensor Networks (WSNs) due to unfavorable environmental conditions that sensor nodes are placed into and some other reasons, power limitation of sensor nodes is the main challenge. Emerging in-network aggregation techniques are increasingly being sought to overcome this limitation and to save energy. Data aggregation methods can be facilitated by cluster based communication model. One application of WSN is in measuring the generated signal from the object. In order to achieve full coverage, this application requires spatially dense deployment of sensor nodes and sensors observations have spatial correlation. Rate-Distortion (RD) theory as an aggregation technique can use spatial correlation to reduce the 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 effective. Numerical test results show the effectiveness of this analysis for data aggregation of moving object using RD theory.