Reduction of Search Space of Unmanned Aerial Vehicles Using Improved Swarm Based Algorithm

This research work proposes a novel approach to eliminate the problem of congestion control in UAVs by applying a hybrid swarm based algorithm to reduce the search space. Congestion plays a crucial role in communication. Search space reduction enables the data transfer in a reliable and efficient manner. It is one of the examples of combinatorial optimization. The objective of this hybridization is to retrieve the best qualities of the Particle Swarm Optimization (PSO) and the Artificial Bee Colony (ABC) algorithm. This study assesses the effectiveness of the suggested strategy by simulating its use and find that it significantly reduces the search space for congestion control in UAVs. Further, the new algorithm is compared with individual capabilities of PSO and ABC, and the performance of the hybrid algorithm has been significantly higher. One of the findings of this is to point the solution, which has the potential to reduce the search space for UAV congestion management and improve the effectiveness and dependability of UAV communication.