<p>It is proven that an optimization algorithm cannot always perform well across various applications because the search mechanisms differ in various algorithms, and the optimization problem space itself has diverse complexities. In this paper, a novel algorithm called the "Bog"(BA) is introduced. This algorithm, for the first time, utilizes mechanisms from plants, insects, and water runoff. It also integrates other metaheuristic methods aimed at improving efficiency in clustering wireless sensor networks. The results show that the proposed method performs better than other algorithms, including the Flower Pollination Algorithm, Dragonfly, Grasshopper, and Flow Direction, all of which are incorporated into its structure. In test functions, its performance in network clustering leads to an increase in the network lifetime to 3100 s, a packet delivery rate of 0.96 gigabits, and a two percent reduction in energy consumption. The results indicate that the proposed method takes longer for the first network sensor to lose its energy, making it a suitable solution for applications where the performance of all sensors is critical.</p>