Performance of Data Reduction Algorithms for Wireless Sensor Network (WSN) using Different Real-Time Datasets: Analysis Study

This paper investigates the effect of data reduction methods in performance Wireless Sensor Network (WSN) using a variety real-time datasets. The simulation tests are carried out MATLAB for several reducing quantity sent data. These approaches Data Reduction based - Neural Fitting (NNF), Time Series (NNTS), Linear Regression with Multiple Variables (LRMV), – “An Efficient Collection and Dissemination (EDCD2)” Fast Independent Component Analysis (FICA). selected algorithms NNF, NNST, EDCD2, LRMV, FICA evaluated indicators included energy consumption, accuracy, percentage. research results show that algorithm helps to reduce amount transferred consumed energy, but each performs differently depending on dataset used.