# Energy Efficient Clustering Protocol for FANETS Using Moth Flame Optimization
## 2 Background and Motivation
### What's the Roles of Bioinspired Algorithms in FANETs?
LEACH was developed to ensure balanced energy use and improve WSN efficiency by dividing the network into numerous clusters and rotating the CHs. LEACH is a MAC protocol based on TDMA, the first hierarchical routing protocol to use clustering. LEACH is a routing system based on clustering, where nodes form different clusters. Every cluster has a CH node that gathers data from cluster members and transmits it to the sink. The LEACH protocol [28]is divided into turns, each of which has two primary stages: setup and data transmission. The setup stage comprises selecting CHs, clustering, and creating the TDMA schedule for data transmission, which is carried out in the data transmission stage. LEACH-C picks CHs based on node residual energy and generates clusters accordingly in the network. As the name implies, LEACH-C [29] employs a centralized technique to choose the best candidate for CH from nominated nodes. Initially, sensor nodes report their remaining energy and position to the sink. The sink computes the average energy of nodes using this data. Then it chooses which nodes will be CHs. Thus, nodes with more leftover energy than average will be chosen as CHs in this round. The rest, however, remains a simple node. Centralization improves CH distribution and selection and the number of communications between nodes and sinks, which improves the network life-cycle. Like LEACH, LEACH-C transfers data to the sink in a single hop, reducing CH lifespan. The number of CHs varies from turn to turn in the LEACH technique, but in the LEACH-C approach, it is fixed. CBLADSR (cluster-based location aided dynamic source routing) is a new routing technique suggested by [PERSON] et al. [8]. Using three parameters, CBLADSR selects the CHs. A CH will be chosen among cluster members with a low-speed ratio, a high energy level, and several neighbor nodes. Each node in the cluster has a neighbor table, which keeps track of all of the other nodes in the group. To communicate between clusters, CBLADSR employs short and long-range transmissions. As part of their research, [PERSON] and [PERSON] [11] came up with an algorithm for mobility prediction. Each node keeps track of its one-hop neighbors in a neighbor table. The neighbor table also contains the probability of how long a node will remain in its table. A dictionary tree structure is used to calculate the probability. This neighbor node's probability and time determine when the link will end. Neighboring nodes' LET probabilities and degrees are used to create a weight for each node. A CH will be chosen from among the nodes based on the node's weight [10; 11; 12; 13]. Figure 5: Spiral flying path. Clustering in ad-hoc networks has also been performed using artificial intelligence approaches such as ant colony optimization (ACO) [17; 20], particle swarm optimization (PSO) [13; 18], and grey wolf optimization (GWO) [14]. Numerous options are generated by using these methods. Nodes that potentially serve as CHs are included in each solution. The future orientation of ad-hoc networks was also examined by [PERSON] et al. [15] and [PERSON] et al. [16]. In addition, these ideas are based on the nodes' mobility. [PERSON] et al. [23] discussed the routing method using the fuzziness in wireless multi-hop networks. [PERSON] et al. [19] came up with a way to choose a CH by a recommendation system that takes information from many different datasets and suggests an optimal CH node. As a result of this research, [PERSON] et al. [20] developed a clustering technique based on the ACO (CACONET). ACO employs the social behavior of ants to find some food or a solution to a shared problem [17]. Another ACO-based algorithm called ACONET [20] has also been used as a clustering technique but has the same problem as [19; 20; 23]. GWOCNETs [25] simulate the grey wolf's leadership hierarchy and hunting strategy. Alpha, beta, delta, and omega are the four varieties of grey wolves. The alpha wolf is the most powerful in a pack and serves as the pack's leader.