Optimizing Power Consumption in Wireless Sensor Networks for Prolonged Sustainability
C. Sivasankar, E. K. Subramanian, V. Sarala, Anush K. Moorthy, N. Purushothaman
Abstract
As Wireless Sensor Networks (WSNs) grow rapidly, power optimization for sustainability and efficiency is needed. This study offers a complete energy-saving and WSN-extending method. Hardware optimization, software algorithms, network management, adaptive network design, AI-based optimization, security, and reliability are advised. Hardware optimization creates energy-efficient low-power sensor nodes. Battery power and solar cells and vibration energy harvesters form a hybrid energy system. It conserves node energy and prolongs network life. The method uses algorithms and software. To save energy, intelligent duty cycle and power management algorithms optimize sensor activity and sleep. Aggregating and compressing data saves transmission and processing energy. These technologies reduce data handling power to improve network efficiency. Optimizing energy use involves network management. Energy-aware routing techniques and multi-hop routing optimize data transmission paths and reduce network layer energy use. To save energy, cross-layer optimization merges programs across network protocol stack levels. Scalable, adaptive network architecture efficiently handles more sensor nodes. Network configuration adapts to energy and environment. Network infrastructures must be scalable and adaptable for energy efficiency. Advanced machine learning and AI-based optimization are used. Machine learning algorithms forecast energy use and needs in predictive energy management. AI optimises energy use in self-optimizing networks, enhancing efficiency. Security and reliability impact energy efficiency. Energy-efficient secure connection protects data. Fault-tolerant networks handle node failures and communication disruptions without affecting energy utilization. It ensures energy economy and network reliability. This method could work. We anticipate 40% reduced node energy use and 75% longer network longevity. Data transmission efficiency should rise by 28.6% and system dependability by 18.75%. Results show that the proposed technique improves WSN efficiency and sustainability.