HaarWavelet Based Distributed Predictive Target Tracking Algorithm for Wireless Sensor Networks

Target tracking is a typical and important application of wireless sensor networks (WSNs). In the consideration of scalability and energy efficiency for target tracking in large scale WSNs, it has been employed as an effective solution by organizing the WSNs into clusters. However, tracking a moving target in cluster-based WSNs suffers many problems e.g. energy consumption and need to use complex predictive tracking. In this paper, we propose a novel scheme, called Haar wavelet-based target tracking (HWDPT). We proposed an efficient prediction algorithm for mobile targets tracking based on Haar Wavelet transform. Also, we integrated on-demand dynamic clustering into a clusterbased WSN for effective target tracking. The simulation results validate that the proposed HWDPT protocol performs better in terms of track failed ratio, energy waste ratio and algorithm complexity, respectively.

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