A High-Robust Sensor Activity Control Algorithm for Wireless Sensor Networks

In wireless sensor networks, it is important to use the right number of sensors to optimize the network and consider the key design and cost. Due to the limited power of sensors, important issues include how to control the state of the sensor through an automatic control algorithm and how to power-save and efficiently distribute work. However, sensor nodes are usually deployed in dangerous or inaccessible locations. Therefore, it is difficult and impractical to supply power to sensors through humans. In this study, we propose a high reliability control algorithm with fast convergence and strong self-organization ability called the sensor activity control algorithm (SACA), which can efficiently control the number of sensors in the active state and extend their use time. In the next round, SACA considers the relationship between the total number of active sensors and the target value and determines the state of the sensor. The data transmission technology of random access is used between the sensor and the base station. Therefore, the sensor in the sleep state does not need to receive the feedback packet from the base station. The sensor can achieve true dormancy and power-saving effects. The experimental results show that SACA has fast convergence, strong self-organization capabilities, and power-saving advantages.