# Robust Clustering Routing Method for Wireless Sensor Networks Considering the Locust Search Scheme
## 1 Introduction
Due to its high application potential, several metaheuristic methods have been introduced in the literature. Some of the most popular metaheuristic schemes involve schemes such as the Differential Evolution (DE) method [8], Genetic Algorithms [9], the Particle Swarm Optimization (PSO) [10], the Artificial Bee Colony (ABC) algorithm [11], the Gravitational Search Algorithm (GSA) [12], and the Grey Wolf Optimizer [13], to name a few. Metaheuristic methods do not assume continuity differentiability, convexity, or determined initial conditions. These properties represent the most important advantages in comparison to other optimization approaches. Although these schemes produce interesting results, they maintain different difficulties when used to solve high multimodal formulations. The Locust Search (LS-II) [14] scheme is a metaheuristic technique extracted from the modeling of the biological behavior of the desert locusts. A locust entity behaves considering two opposite processes: solitary and social. Under the solitary process, elements avoid being in contact with other entities with the objective to explore new promising areas for food sources. On the other hand, the social process considers the high concentration of the entities to consume the areas with abundant food resources. This mechanism of concentration involves the attraction of entities located in areas of low food levels to those elements that are in positions with the best food sources. With the combination of both behaviors, the LS-II approach presents very effective global and local search properties. These characteristics have motivated its use in a wide variety of complex optimization formulations such as parameter estimation of chaotic systems [15], image processing [16], and pattern recognition [17], to name a few. In this paper, a novel clustering routing protocol for Wireless Sensor Networks is presented. The approach is designed based on the Locust Search (LS-II) method. In the proposed protocol, the number of cluster head nodes and their selection is identified by the LS-II approach. Once cluster heads nodes are selected, the rest of the sensor nodes are assigned to their nearest cluster head. Under such conditions, the network structure is constantly modified by the LS-II until finding the optimal distribution of the node structure that reduces the transmission distance. Numerical simulations exhibit competitive configurations, which demonstrate that our routing protocol obtains minimal energy consumption, improving the lifetime and extending the stability period of the network in comparison with other popular clustering routing protocols. The main contributions of this research can be summarized as follows: (1) a new clustering routing protocol for Wireless Sensor Networks is proposed, (2) the scheme translates the clustering routing task in an optimization formulation, (3) the solution of the optimization problem (number of cluster head nodes and their selection) is identified by the Locust Search (LS-II) method which has never been used for these purposes. The next sections of the paper are structured as follows. In Section 2, the related work is discussed. In Section 3, the main characteristics of the Locust Search (LS-II) method are analyzed. Section 4 explains our clustering protocol. Section 5 exhibits the numerical simulations of our protocol compared with other well-known methods. Finally, the conclusions are discussed in Section 6.