A Survey of Power Reduction Techniques for Ad-Hoc Wireless Sensor Networks

Abstract

Wireless sensor networks (WSN) are the promising technology for telecommunication and network industry. It is provided with great potential to solve the number of problems in battlefields and other commercial applications such as traffic surveillance, health controlling, environment monitoring, construction structures, smart homes and offices. Large number of very small size, low cost, low power multifunctional sensor nodes constitute the WSN. These sensors sway the understanding of the physical world by sensing, processing and transmitting the data. The above functions are highly influenced by factors such as power, energy and lifetime of the sensor nodes. This technical paper explores various low power design architectures like reconfigurable hardware, sleep walker, variable dual VDD, modular architecture and folded tree architecture by presenting a comprehensive survey concerning passive and active power control mechanisms in WSN with investigation of the existing solution and evaluation.

Introduction

Wireless Sensor Networks (WSNs) are widely used for applications in military, agriculture, biomedical, environmental, and structural monitoring. These systems rely on sensor nodes composed of sensors, microcontrollers, radios, and power supplies—usually batteries. However, radio transmission is energy-intensive, making low-power design critical to extend node lifetime, especially in remote and inaccessible locations.

Key Challenges:

• Limited battery life

• Infeasibility of frequent replacements

• Unreliable renewable sources like wind/solar

• Need for efficient, sustainable, and compact designs

Core WSN Node Components:

1. Sensing Unit

2. Processing Unit

3. Transceiver

4. Storage Unit

5. Power Unit

6. Power Generator

Techniques for Reducing Power Consumption:

• Duty cycling: Minimize active time

• Dynamic frequency/voltage scaling

• Radio tuning

• Selective functional module activation

• Energy-efficient FPGAs (e.g., Xilinx, Altera)

Survey of Low-Power WSN Architectures:

A. SNOC Architecture (Dynamic Voltage Scaling - DVS)

• Developed by Robert X. Gao et al

• Uses DVS to adjust voltage & clock speed based on task demands

• Reduces energy consumption by 43% over fixed-power systems

• Modular & flexible software design allows in-situ adaptation

B. ASIC-Based Design (Sleep-Event Wakeup)

• Proposed by Shilong Lu et al

• Uses external oscillator and interrupt-based wakeup

• Divides clock into power-level slots

• Power modules turned on/off individually to save energy

C. Reconfigurable Hardware Design (FPGA + ICAP)

• Developed by Y. Li et al

• Uses partial dynamic reconfiguration via ICAP in Xilinx FPGAs

• Saves 31–829 mW depending on implementation

• Efficient data/control flow through BRAM and UART/ZigBee

D. Modular 3D Cube Architecture

• Developed by Rafael et al

• Compact, miniaturized 6-module cube structure

• Each sub-module handles specific functions (e.g., sensing, power)

• Flexible, modular bus-based interconnection using flex PCBs

E. SRAM-FPGA-Based Vision Sensor Node (VSN)

• Designed by Muhammad Imran et al

• SRAM-based FPGA is more power-efficient than FLASH-based

• Enters sleep state with only RTC active after task completion

• 670 mW average power consumption, ~3.2 years MCU lifespan

F. Near-Threshold Design for Biomedical WSN

• Proposed by Jos Hulzink et al

• Uses SIMD, multi-layer clock gating, and 15 power domains

• Processor and memories can independently switch on/off

• Achieves 13 pJ/cycle for single-lead ECG application

G. Variable Dual-VDD Reconfigurable Processor

• Developed by Jianfeng Zhu et al

• Utilizes dual voltage levels (VDDH, VDDL) selectively for interconnects

• Controlled via compiler and buck converter

• Achieves 1.2 μW power at 0.7V, highly efficient interconnect-level design

Conclusion

Power consumption is the vital factor to be considered in recent years, many researches are concentrating on low power architectures. Power consumption influences the performance and the lifetime of the sensor nodes in WSN. Various design architectures are surveyed and compared in this technical paper in terms of power and energy consumption. The above surveyed papers present the low power design along with other features such as lifetime enhancement, low area complexity.

References

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Copyright

Copyright © 2025 Dr. M. Vijayakumar, S. Mahendran, S. Priyadharshini, P Mohanraj. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.