# Arithmetic Optimization AOMDV Routing Protocol for FANETs
###### Abstract
Due to the characteristics of UAVs, such as fast node mobility, limited energy, dynamic topology, and complex environment, communication between UAV nodes needs to have high reliability and energy efficiency so that the flying formation can make an appropriate flight control strategy for flight formation. Therefore, many studies have proposed meta-heuristic-based routing protocols that use the ant colony [30], particle swarm [31; 32], whale [33], and genetic [34] to find the optimal path with higher energy efficiency. Most of the meta-heuristic algorithms proposed as routing protocols for FANETs have been proposed as a hybrid with the known multi-path routing protocols as the ad hoc on-demand multi-path distance vector (AOMDV) and MP-DSR. Their objective is to achieve a balance between the shortest path, load balancing, and energy conservation of nodes in order to reduce the number of dead nodes and the network overhead, thereby obtaining the optimal route. Arithmetic optimization (AO) [35] has been one of the most investigated meta-heuristic optimization algorithms in the last two years in different fields, including solving mechanical engineering design problems [36], damage assessment in composite plates [37], robot path planning [38], and image thresholding [39]. As far as we know AO has not been investigated before as a routing protocol in FANETs. In this study, we propose an energy-efficient hybrid routing protocol called the arithmetic optimization (AO)-based AOMDV (AO-AOMDV) by utilizing the powerful meta-heuristic algorithm AO. The protocol has demonstrated highly promising results in various research studies, indicating its significant potential. Although there are variations of meta-heuristic algorithms in the field of population-based optimization methods, their optimization processes generally consist of two main stages: exploration and exploitation. The former refers to the extensive use of algorithmic search agents to cover the search space, thereby avoiding local solutions. The latter improves the accuracy of the solutions obtained during the exploration phase. In this paper, we introduce a new fitness function on the basis of the AOMDV routing protocol to replace the minimum hop count decision mechanism. Additionally, we propose the utilization of arithmetic optimization to rapidly find the optimal path from paths with different fitness values. We refer to the routing protocol described above as AO-AOMDV. AO-AOMDV incorporates not only the fitness function but also employs arithmetic optimization. The fitness function is utilized to provide the decision mechanism, while arithmetic optimization is dedicated to swiftly implementing the decision mechanism. Within AO-AOMDV, we select the most suitable route from the source to the destination based on three parameters. The chosen route should exhibit relatively high link stability and residual energy while having comparatively lower traffic to avoid congestion. The structure of the paper is organized as follows: Section 2 covers a survey on the literature review. Section 3 presents the routing issues encountered in the current phase of UAV development. It elaborates on the fitness function and explains the solution by describing the routing discovery and maintenance process. Section 4 outlines the performance evaluation and presents the experimental results. Finally, Section 5 concludes the research outcomes.