Optimization of Sensor Node Placement in Wireless Sensor Networks using the Chimpanzee Leader Election Optimization

In Wireless Sensor Network (WSN), sensor node positioning is an essential factor that affects network performance and efficiency. Optimal positioning of sensor nodes and sinks can improve communication quality, reduce energy consumption, and extend network lifetime. Without proper placement, sensor networks can quickly run out of power, resulting in decreased performance and short operational time. Therefore, it is essential to optimize sensor node placement to extend the lifespan of WSNs. This study aims to maximize sensor node placement using the Chimpanzee Leader Election Optimization (CLEO) algorithm. This algorithm works by utilizing the concept of leader election in a group of chimpanzees to efficiently place sensor nodes and sinks. The experimental results show a significant relationship between the distance of the sensor node to the sink and the energy capacity of the sensor node in determining the optimal position. Placing nodes closer to the sink reduces energy consumption while selecting a position that considers the sensor node’s energy capacity, which can extend the network lifespan. These findings prove that CLEO can be used as an effective solution in optimizing WSN performance and lifetime.