Wireless sensor networks (WSN) are network that are constructed using number of sensor nodes distributed and connected wirelessly to perform some specific applications. These networks are strictly restricted in the usage of energy as they use batteries with finite amount of power. This necessitates the need for data compression at each sensor node in a WSN so as to overcome the resource constraints of the network and increase its lifetime. Various functions carried out by each node are sensing, processing, communicating and storing the data, among which the communication consumes much energy than the other functions. Data compression is one technique that extends the network lifetime by reducing the energy consumed at each node during communication. The proposed work comprises of 5 different methods that suggests modification of lossless Rice Golomb Coding (RGC) compression algorithm with respect to the decision of tunable parameter based on preprocessing of the input data. Simulation results on various modifications of RGC using different datasets in MATLAB software is analyzed and compared with respect to root mean square error (RMSE) and saving percentage (SP). The modified lossless compression algorithm EMARGC_D with better saving percentage is applied and executed in real time using NI WSN nodes interfaced with LabVIEW.
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