Chen, W.; Tang, F.; Cui, F.; Chen, C. Research on Energy Harvesting Mechanism and Low Power Technology in Wireless Sensor Networks. Sensors2024, 24, 47.
Chen, W.; Tang, F.; Cui, F.; Chen, C. Research on Energy Harvesting Mechanism and Low Power Technology in Wireless Sensor Networks. Sensors 2024, 24, 47.
Chen, W.; Tang, F.; Cui, F.; Chen, C. Research on Energy Harvesting Mechanism and Low Power Technology in Wireless Sensor Networks. Sensors2024, 24, 47.
Chen, W.; Tang, F.; Cui, F.; Chen, C. Research on Energy Harvesting Mechanism and Low Power Technology in Wireless Sensor Networks. Sensors 2024, 24, 47.
Abstract
Wireless sensor networks (WSN) are widely used in various fields such as military, industrial and transportation for real-time monitoring, sensing and data collection of different environments or objects. However, the development of WSN is hindered by several limitations, including energy, storage space, computing power and data transmission rate. Among these, the availability of power energy plays a crucial role as it directly determines the lifespan of WSN. To extend the life cycle of WSN, two key approaches are power supply improvement and energy conservation. Therefor, we proposed an energy harvesting system and a low energy consumption mechanism for WSN. Firstly, we delved into the energy harvesting technology of WSN, explored the utilization of solar energy and mechanical vibration energy to ensure a continuous and dependable power supply to the sensor nodes, and analyzed the voltage output characteristics of bistable piezoelectric cantilever. Secondly, we proposed a neighbor discovery mechanism that utilizes a separation beacon, is based on reply to ACK, and can facilitate the identification of neighboring nodes. This mechanism operates at a certain duty cycle ratio, significantly reduces idle listening time and results in substantial energy savings. In comparison to the Disco and U-connect protocols, our proposed mechanism achieves a remarkable reduction of 66.67% and 75% in the worst discovery delay, respectively. Furthermore, we introduced a data fusion mechanism based on integer wavelet transform. This mechanism effectively eliminates data redundancy caused by spatio-temporal correlation, results in a data compression rate of 5.42. Additionally, it significantly reduces energy consumption associated with data transmission by the nodes.
Keywords
wireless sensor networks; energy harvesting; neighbor discovery; data fusion
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright:
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.
