Feasibility and Efficacy of Modified Adaptive Rice Golomb Coding for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are made of many battery‑powered sensors spread out in space that monitor physical or environmental conditions. Because each sensor has limited energy, saving power is essential for extending the network’s lifetime. The radio module usually consumes the most power, so cutting the amount of data sent by using good compression can save a lot of energy. This project investigates the Modified Adaptive Rice Golomb Coding (MARGC) algorithm, which is designed for low‑resource sensor nodes. MARGC adjusts its coding parameters on the fly to match the statistical properties of the incoming sensor data, delivering high compression ratios with only a small computational load. The project provides code

for simulating the algorithm on a variety of environmental data sets and includes guidance for real‑time deployment on hardware such as National Instruments Wireless Sensor Network (NI WSN) devices. Performance is evaluated in terms of compression ratio, computational complexity, and energy savings, showing that MARGC is a practical solution for energy‑efficient data transmission in modern WSNs.

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