Ant Lion Optimizer Based Clustering Algorithm for Wireless Body Area Networks in Livestock Industry

Wireless Body Area Networks (WBANs) are emerging in the livestock industry for remote monitoring of cattle using wireless body sensors (WBS). The random mobility animals acting as nodes causes network’s topology to change rapidly, originating from scalability and reliability issues. Stable transmission acquired data base station requires an intelligent clustering mechanism that reduces energy consumption fulfills constraints. Several techniques available a solution, but these yield numerous cluster heads, resulting more utilization. Higher utilization lessens effective life WBSs increases costs. This paper presents metaheuristic approach selecting optimal clusters WBANs realize energy-efficient routing protocol health behavior monitoring. proposed employs Ant Lion Optimizer (ALO) select different pasturage sizes ranges considering user’s preferences about density. technique with ALO is compared other recent such Colony Optimization, Grasshopper Moth Flame Optimization. comparison results show technique’s effectiveness realizing protocols applications.