Energy Efficient Prediction-Based Clustering Algorithm for Target Tracking in Wireless Sensor Networks

Nowadays energy efficiency has been a main challenge in wireless sensor networks (WSNs) and their applications. Target tracking is one of the most important of these applications. In this paper we propose an energy efficient prediction-based clustering algorithm for target tracking in WSNs. Our algorithm attempts to decreases transmission distance between transmitter and receiver nodes and decreases the number of transmitted packets. Also proposed algorithm uses a prediction-based method. Prediction-based methods, with prediction the target trajectory and its next location, only activate special nodes of network for tracking and rest of nodes remain in sleep mode for energy saving. Simulation results show that our algorithm has better performance in energy efficiency from other prediction-based methods which leads to higher lifetime.