Multi-objective coverage optimization in SDWSN based on hybrid dung beetle Optimization algorithm

Abstract With the rapid development of IoT technology, smart aprons play a key role in smart civil aviation. However, challenges remain in balancing connectivity and coverage in SDWSN (Software-Defined Wireless Sensor Networks) deployments. To address this, a hybrid optimization strategy based on the dung beetle algorithm was developed. This algorithm simulates the dung beetle’s rolling and dancing action, incorporates biomimetic optimization strategies, and utilizes table-driven methods and decision trees under the SDWSN global view control architecture to optimize network performance. The experimental results show that, compared to other algorithms of the same type, this algorithm has a higher network coverage and ensures complete network connectivity, providing reliable network support for SDWSN in apron scenarios.