# Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol
###### Abstract  
A Flying Ad-hoc network constitutes many sensor nodes with limited processing speed and storage capacity as they institute a minor battery-driven device with a limited quantity of energy. One of the primary roles of the sensor node is to store and transmit the collected information to the base station (BS). Thus, the life span of the network is the main criterion for the efficient design of the FANETS Network, as sensor nodes always have limited resources. In this paper, we present a methodology of an energy-efficient clustering algorithm for collecting and transmitting data based on the Optimized Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. The selection of CH is grounded on the new optimized threshold function. In contrast, LEACH is a hierarchical routing protocol that randomly selects cluster head nodes in a loop and results in an increased cluster headcount, but also causes more rapid power consumption. Thus, we have to circumvent these limitations by improving the LEACH Protocol. Our proposed algorithm diminishes the energy usage for data transmission in the routing protocol, and the network's lifetime is enhanced as it also maximizes the residual energy of nodes. The experimental results performed on MATLAB yield better performance than the existing LEACH and Centralized Low-Energy Adaptive Clustering Hierarchy Protocol in terms of energy efficiency per unit node and the packet delivery ratio with less energy utilization. In addition, the First Node Death (FND) is also meliorated when compared to the LEACH and LEACH-C protocols. clustering; energy consumption; FANETS; IoT; LEACH; routing protocol; wireless sensor network +
Footnote †: journal:  
0000-0001-9901-9901-9901-9901-9901-9901-9901-9901-901-9901-9901-901-901-9901-9901-9 Some micro-sensor nodes also assess parameters such as temperature and pollution, the physical environment, heat emitted, and many more according to the need and deployment. Nodes gather and transmit data to the BS, and then the user will receive information through the internet [1]. WSN has the following objectives:  
1. To monitor and record activities within the supervised area. 2. To detect and record events inside the supervised area. 3. Evaluation based on selected standards and parameters. Usually, WSN is a battery-powered sensor node that is neither rechargeable nor replaceable, and most of the energy is used in gathering, processing, and packet transmission. The limitation of energy consumption is the biggest constraint in WSN. Furthermore, data replication is another limitation that affects and reduces sensor nodes' energy [2]. Thus, saving energy to improve network life is also a priority for WSN. The routing protocol is the mechanism by which the data can be moved from the source to the destination. It aims to achieve network scalability, a high data transmission rate, and energy consumption efficiency. Various routing protocols were established over recent years to prolong the network's life by reducing the power usage by WSN. The proposed routing protocols rely upon multiple metrics, such as the communication model, the structure of the network, and topology [1; 2; 3]. Clustering uses the data aggregation [2] feature to balance energy as WSN employs clustering routing protocols to achieve energy efficiency. Clustering also reduces the number of routing packets. It provides greater scalability, lower load, minimum energy usage, data aggregation, crash prevention, load balancing, latency step-down, failure resilience, greater robustness, communication assurance, and network life maximization. FANETs are a form of Ad-hoc network configuration of unmanned aerial vehicles (UAVs). UAVs track a particular region by taking pictures, gathering other details based on their sensors, and transmitting them to the BS as a UAV-to-ground (U2G) communications system. Unlike traditional cable infrastructure used in general topology, FANETs require more critical challenges in the context of topology:  
1.