Enhancing the Performance of Wireless Sensor Networks Using Low Power Design

Authors: N. Mahendran, R. Madhuranthi

Abstract:

Wireless sensor networks (WSNs), are constantly in demand to process information more rapidly with less energy and area cost. Presently, processor based solutions have difficult to achieve high processing speed with low-power consumption. This paper presents a simple and accurate data processing scheme for low power wireless sensor node, based on reduced number of processing element (PE). The presented model provides a simple recursive structure (SRS) to process the sampled data in the wireless sensor environment and to reduce the power consumption in wireless sensor node. Based on this model, to process the incoming samples and produce a smaller amount of data sufficient to reconstruct the original signal. The ModelSim simulator used to simulate SRS structure. Functional simulation is carried out for the validation of the presented architecture. Xilinx Power Estimator (XPE) tool is used to measure the power consumption. The experimental results show the average power consumption of 91 mW; this is 42% improvement compared to the folded tree architecture.

Keywords: Power consumption, energy efficiency, low power WSN node, recursive structure, sleep/wake scheduling.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1127533

References:

[1] Nikolaos A. Pantazis, “A survey on power control issues in Wireless sensor networks” IEEE communications, Volume 9, No. 4, 4th Quarter 2007.
[2] S. G. Shiva Prasad Yadav, “Wireless Sensor Networks - Architectures, Protocols, Simulators and Applications: A Survey” International Journal of Electronics and Computer Science Engineering, ISSN- 2277-1956.
[3] Parool Jain,” A survey on energy optimization in wireless sensor network” International Journal of Engineering Sciences & Emerging Technologies, ISSN: 2231 – 6604 Volume 5, Issue 1, pp: 68-74, Apr. 2013.
[4] Dhanajay A. Sabale, Sushil M. Sakhare, “Wireless Sensor Network for Industrial Process Controlling & Monitoring” International Journal of Electronics Communication and Computer Technology (IJECCT) Volume 4 Issue 4 (July 2014).
[5] N. Mahendran, Dr. S. Shankar, “Performance Evaluation of Scheduling Schemes in Wireless Sensor Networks”, International Journal of Applied Engineering Research, ISSN 0973-4562, Volume 10, Number 31 PP: 23326-23330, 2015.
[6] Robert X. Gao, “Architectural Design of a Sensory Node Controller for Optimized Energy Utilization in Sensor Networks”, IEEE transactions on instrumentation and measurement, vol. 55, no. 2, April 2006.
[7] Shilong Lu, Xi Huang, Li Cui, “Design and Implementation of an ASIC-based Sensor Device for WSN Applications”, IEEE Transactions on Consumer Electronics, Vol. 55, No. 4, November, 2009.
[8] Y. Li Z. Jia F. Liu S. Xie,"Hardware reconfigurable wireless sensor network node with power and area efficiency", IET Wirel. Sens. Syst., 2012, Vol. 2, Iss. 3, pp. 247–252.
[9] Rafael Vicente Martinez-Catala, "A Modular Wireless Sensor Platform with Fully Integrated Battery", IEEE transactions on components and packaging technologies, vol. 32, no. 3, September 2009.
[10] Muhammad Imran, "Energy-Efficient SRAM FPGA-Based Wireless Vision Sensor Node: SENTIOF-CAM", IEEE transactions on circuits and systems for video technology, vol. 24, no. 12, December 2014.
[11] Jos Hulzink, "An Ultra Low Energy Biomedical Signal Processing System Operating at Near-Threshold", IEEE transactions on biomedical circuits and systems, vol. 5, no. 6, December 2011.
[12] Jianfeng Zhu et al, "Low-Power Reconfigurable Processor Utilizing Variable Dual VDD", IEEE transactions on circuits and systems—ii: express briefs, vol. 60, no. 4, April 2013.
[13] Cedric Walravens, “Low-Power Digital Signal Processor Architecture for Wireless Sensor Nodes”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 22, no. 2, February 2014.