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

Abstract In wireless sensor networks, it is important to use the best number of sensors to optimize the network and consider the key design and cost. Owing to the limited power of sensors, how controlling the state of the sensor through an automatic control algorithm and power-saving and efficient distribution of work have become important issues. 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 sensor activity control algorithm (SACA), which can efficiently control the number of sensors in the active state and extend their use time. SACA considers the relationship between the total number of inactive sensors and the target value and determines the state of the sensor in the next round. 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.