## 1 Introduction  
The Internet of Things (IoT) is an emerging technology that plays an essential role in the efficiency and productivity of our everyday lives, among various other aspects. This technology has attracted the attention of both academics and industry members. The term IoT was coined in 1990 by [PERSON] [1; 2; 3]. IoT refers to a group of physical objects, namely, vehicles, machines, buildings, and other devices, that are connected to the Internet to transfer data to other participants in the network. A wide range of applications adopt IoT features, including transportation, smart healthcare, agriculture, and smart homes [4; 5; 6]. Sensor nodes in wireless sensor networks (WSNs) are geographically distributed to communicate and transmit data to each other. These sensors detect humidity, temperature, smoke, and other physical and environmental factors. Sensor nodes are designed to perform sensing, processing, and analysis of received data [7; 8; 9]. Sensor nodes have been enhanced with low power consumption owing to recent technological advancements of WSNs in, e.g., industrial automation and agriculture. In WSN applications, sensor nodes are distributed and managed using efficient computational algorithms. The network structure of sensor nodes changes owing to external factors. Consequently, sensor nodes face challenges, such as routing processes, data loss, limited processing power, and localization. The overall performance of a network can be enhanced by redesigning the network topology in a WSN [10; 11; 12]. WSN technology has been adapted to various emerging applications. Sensor nodes are low-power devices that operate using batteries. The energy consumption of sensors depends on multiple factors, including the type of routing protocol, distance between transmission nodes, and transmission packet size [13; 14]. This affects the overall network performance. To avoid an energy-efficiency problem, an optimal routing protocol is required to maintain energy equally among every node in a network. The optimal routing protocol is adapted depending on the application requirements and network characteristics to improve the network lifetime [15; 16]. Cluster head (CH) selection is a practical approach for forming a group of nodes as clusters in a WSN. A CH node consumes more energy than other cluster members (CMs) in a network. Various challenges, such as dynamic environment conditions, network scalability, and energy constraints, necessitate CH selection in the network. The designated CH in the cluster aims to collect and transmit data to a central node or base station in the network [17; 18]. The CH consumes more energy than any other nodes in a cluster. Therefore, it is essential to select an optimal CH for a cluster by employing optimization techniques to ensure network stability and energy consumption [19; 20]. The CH is chosen based on various network parameters, such as the remaining energy and distance between nodes, to improve the overall network performance. Several methods have been proposed for the CH selection [21; 22; 23]. An optimization algorithm is a mathematical computational technique used to determine the optimal solution for a given objective function. It is primarily used in the engineering field, particularly in the network field. Optimization algorithms execute many iterations to obtain appropriate solutions. Many existing optimization algorithms are available, including the cuckoo search (CS), honey bee mating optimization (HBMO), cat swarm optimization (CSO), whale optimization algorithm (WOA), harmony search (HAS), tabu search algorithm (TSA), and deferential evolution algorithm (DEA). However, most optimization algorithms require slightly longer convergence times during many rounds of iteration. To solve this problem, we propose a COA optimization algorithm to enhance network lifetime and throughput. This study mainly focused on the following major research contributions:  
* A substantial analysis was conducted on the proposed EACH-COA technique to obtain the best CH in a network.