# Routing Selection Algorithm for Mobile Ad Hoc Networks Based on Neighbor Node Density
## 1 Introduction  
### Background  
With the rapid development of society, there is an increasing demand for wireless connectivity, and the required quality is becoming higher [1, 2]. Generally, wireless networks can be categorized into two types: infrastructure-based networks, which are typically controlled by a central network such as GSM (Global System for Mobile Communications), IoT (internet of things) [3], or Wi-Fi, and infrastructureless networks, which consist of a network of interconnected devices without a central controlling node, e.g., ad hoc networks. Mobile ad hoc networks [4] fall under the category of ad hoc networks and represent a type of wireless network. Comprising a set of mobile nodes, they have the capability to autonomously establish a network without the need for preconfigured infrastructure. Furthermore, they can create instantaneous communication networks without an internet connection. These nodes interconnect through self-organization and distributed methods to facilitate the exchange of information and data. Mobile ad hoc networks were initially developed for military applications, but they are now widely used in various fields such as emergency medical response, unmanned aerial vehicles (UAVs), and self-organizing sensor networks. Mobile ad hoc networks have several advantages. 1. Damage resistance: As a decentralized network, mobile ad hocnetworks do not rely on single nodes. This means that even if one or more nodes fail or are destroyed, the network can still function properly. This network topology also provides the capability to rapidly adapt to the addition or removal of nodes. 2. Flexibility and Scalability: Mobile ad hoc networks are versatile and can adapt to various types of network environments. These advantages make mobile ad hoc networks very useful in scenarios that require fast deployment, high flexibility, and fast response [5; 6]. However, there are still some challenges and limitations in mobile ad hoc networks. For instance, in scenarios where nodes are moving rapidly, the quick changes in network topology can lead to the failure and recalibration of routing paths. This can result in the failure and recalculation of routing paths, causing some nodes to send a large number of broadcast messages to other nodes within a short period. These messages overlap with the regular messages being transmitted by nodes, resulting in momentary traffic surges and congestion that exceed the network's bandwidth and resource capacity. As a consequence, network performance deteriorates, and in severe cases, it might lead to complete network interruption. This phenomenon is known as a network storm. To address this issue, researchers have developed various strategies and technologies to optimize the performance of mobile ad hoc networks and reduce the risk of network storms. Among these approaches, the most commonly used methods include congestion control and routing protocols, such as AODV (ad hoc on-demand distance vector). These technologies and protocols help reduce unnecessary broadcast messages and optimize routing paths, thereby preventing the occurrence of network storms. With the evolving demands, these methods perform admirably in scenarios with a relatively smaller number of mobile devices. However, as the number of mobile devices increases, network performance often experiences a significant decline. This is because, with the growing number of devices, communication activities within the network become more complex and intensive, leading to issues like network congestion and performance degradation. In ND-AODV, the introduction of neighbor node density serves as a solution. As the number of neighboring nodes increases, the probability of nodes forwarding control information gradually decreases, thereby effectively alleviating network congestion. Nevertheless, this approach does not adequately account for the precise location of the receiving nodes, potentially resulting in unnecessary wastage of network resources.