Data collection algorithm for clustered large-scale wireless sensor networks using virtual nodes

For densely deployed wireless sensor networks, there is a high correlation between multiple sensors in close proximity. In this paper, a data collection algorithm for clustered large-scale wireless sensor networks is proposed. The cluster heads fuse the data of cluster members by polynomial fitting, and transfer the fitting coefficients to base station or other cluster heads. Based on the locations of cluster heads and there fitting coefficients, base station and other cluster heads can construct in their memory numbers of so called “virtual nodes”, by which, the data status of the whole network can be recurred by base station, or in-line data fusion can be implemented by other cluster heads. In this paper, we give the method how to polynomial fit the data in a cluster, how to construct “virtual nodes”, and how to reshow the original data and implement in-line data fusion by “virtual nodes”.