Prediction-based spatial correlation clustering algorithm for efficient data reduction in wireless sensor network

Wireless sensor network (WSN) is adapted in wireless communication for many application area due to its low computational cost. But, WSN has limited lifetime due to its energy conservation during communication between the source and the sink nodes. This energy conservation problem is reduced by the data reduction technique, which decreases the redundant data transmission. Also the spatial correlation arises in WSN for larger area. Therefore, the scheduling-based spatial correlation is used to increase the coverage area and decrease the energy consumption. However, packet loss occurred during data transmission due to its similar magnitude. Hence, the prediction-based spatial correlation clustering (PSCC) method is proposed for efficient data reduction and maximising effective area. The simulation results illustrate that the proposed method achieves greater enhancement in convergence speed, which provide high data reduction and lesser energy consumption compared with the existing approaches.