Spatio-Temporal Data Correlation with Adaptive Strategies in Wireless Sensor Networks

One of the major task of sensor nodes in wireless sensor networks is to transmit a subset of sensor readings to the sink node estimating a desired data accuracy. Therefore in this paper, we propose an accuracy model using Steepest Decent method called Adaptive Data Accuracy (ADA) model which doesn't require any a priori information of input signal statistics to select an optimal set of sensor nodes in the network. Moreover we develop another model using LMS filter called Spatio-Temporal Data Prediction (STDP) model which captures the spatial and temporal correlation of sensing data to reduce the communication overhead under data reduction strategies. Finally using STDP model, we illustrate a mechanism to trace the malicious nodes in the network under extreme physical environment. Computer simulations illustrate the performance of ADA and STDP models respectively.