Analysis and implementation of novel Rice Golomb coding algorithm for wireless sensor networks

Wireless sensor networks (WSN) comprises of several sensor nodes scattered wirelessly to accomplish a particular task. Each sensor node is empowered by a battery. The various functions of the node namely sensing, computing, storage and transmission/reception of data consumes power from the battery with limited capacity. As these batteries do not last for a long time, an efficient algorithm is required to extend its life time. Data compression algorithm is a unique method adopted to minimize the amount of data being sent or received and thereby reduces the power consumed during communication. This would further increase the lifetime of node and also the network. In this paper a simple lossless compression algorithm is proposed and is also compared with the existing Adaptive Huffman coding algorithm that is been widely used in wireless sensor network applications. The comparative analysis is based on different compression parameters like compression ratio, compression factor, saving percentage, RMSE and encoding & decoding time. The data set for comparison is acquired using a temperature sensor interfaced with NI 3202 programmable sensing node. The comparative analysis is performed and the results are simulated using MATLAB software. The NI WSN nodes are used to execute the algorithm for instantaneous data. The analysis of number of packets transmitted during wireless communication, both before and after compression is performed using Wireshark network analyzer tool. The simulation result shows that the proposed lossless compression algorithm performs better than the existing one. The hardware implementation has proven that the amount of data traffic is reduced after compression which will help in reducing the transmission power and thereby saves the lifetime of the node in a wireless sensor network.