Adaptive Hybrid Bird Swarm Optimization Based Efficient Transmission In WSN.

Networking proposed protocol, programming, node placement, positioning techniques, and data security are just a few of the study disciplines where the System has been used. As a consequence of the superior network topology, nodes may be separated into different clusters. The establishing groupings of device nodes is known as convergence. The persons in charge of all of the groups are known as cluster chiefs (CHs). It is Computationally to reduce total duration using segmenting techniques. The current study provides a hybrid evolutionary algorithm with an adjustable hybridization bird optimizer for successful clustering. The CH approach considers operational costs, as well as residual energy and data rate. According to simulation data, the Adaptive Hybrids Bird Swarm Optimization technique surpasses CL-LEACH and Hybrid Bird Swarm Optimized in terms of packet delay, packet delivery, and network longevity. Finally, AHBSO's speed is crucial that compare with partial swarm optimization, Combination Swarm Optimization, and its results. The proposed technique improves transmission speed by 25.34--35.50 percent depending on node density. [ABSTRACT FROM AUTHOR]