Enhancing Data Compression Efficiency in Wireless Sensor Networks: A Study and Modification of Rice Golomb Coding Algorithm | Chapter 5 | Theory and Applications of Engineering Research Vol. 9

 The chapter suggests improvements to the Rice Golomb Coding (RGC) compression for wireless sensor networks (WSN), focusing on nodes with limited resources. To extend the network's life, effective data compression is crucial, especially for nodes periodically sending data to the sink. Five techniques adapting RGC based on adjustable parameters from preprocessed input data is presented in this chapter. The goal is to reduce energy use during communication in WSN nodes. Using various MATLAB datasets, we compare outcomes, where the EMARGC_D method, with auto-differencing, shows better results. Real-time tests with NI WSN nodes in LabVIEW support the practicality of our approach. This aims to deepen understanding of our findings, particularly in aiding resource-constrained nodes sending data regularly to the sink node.

Author(s) Details:

S. Kalaivani,
Department of Electronics and Communication Engineering, B.S.A Crescent Institute of Science and Technology, Chennai, Tamil Nadu, India.

C. Tharini,
Department of Electronics and Communication Engineering, B.S.A Crescent Institute of Science and Technology, Chennai, Tamil Nadu, India.

Please see the link here: https://stm.bookpi.org/TAER-V9/article/view/13828

Feasibility and Efficacy of Modified Adaptive Rice Golomb Coding for Wireless Sensor Networks | Chapter 2 | Research and Applications Towards Mathematics and Computer Science Vol. 7

Wi-Fi Sensor Networks (WSNs), characterized by energy-forced nodes powered by limited-ability batteries, necessitate energy-effective data compression methods to extend their network lifetime. The ideas module within each sensor node arises as a primary energy services, making data compression a important approach to curtail data broadcast. This paper introduces the Modified Adaptive Edible grain Golomb Coding (MARGC) algorithm as an persuasive compression technique to reinforce the network's lifespan. Simulation results, utilizing various datasets, underscore the feasibility and efficiency of the MARGC algorithm. Furthermore, the invention's real-time exercise on National Instruments Wireless Sensor Network (NI WSN) fittings demonstrates its realistic applicability and performance. To standard our contribution, future work will involve a approximate analysis with existing methods to highlight the superior aspects of the projected MARGC algorithm.

Author(s) Details:

S. Kalaivani,
Department of Electronics and Communication Engineering, B.S.A Crescent Institute of Science and Technology, Chennai, Tamil Nadu, India.

C. Tharini,
Department of Electronics and Communication Engineering, B.S.A Crescent Institute of Science and Technology, Chennai, Tamil Nadu, India.

Please see the link here: https://stm.bookpi.org/RATMCS-V7/article/view/12832