# Enhanced Ant Colony Optimization for Vehicular Ad Hoc Networks Using Fittest Node Clustering
## 1 Introduction  
Routing protocols and clustering techniques play essential roles in the operation of ad hoc networks, including mobile ad hoc networks (MANETs), vehicular ad hoc networks (VANETs), and flying ad hoc networks (FANETs) [1]. These networks require efficient routing to ensure reliable communication, and various intelligent approaches, such as fuzzy logic and artificial bee colony (ABC) optimization, can be used to enhance the performance of routing protocols. Let us discuss different routing protocols and how these intelligent approaches can be applied in the context of MANETs, VANETs, and FANETs [2]. MANETs include ad hoc on-demand distance vector (AODV), a reactive routing protocol that establishes routes only when needed, reducing overhead in the network, and dynamic source routing (DSR), a reactive protocol that maintains a route cache to store frequently used paths, reducing the latency in route discovery. VANETs are designed specifically for vehicular networks considering vehicle positions and speeds for routing decisions. FANETs require specialized routing protocols to account for the mobility and unique characteristics of flying nodes including protocols that consider altitude, 3D space, and dynamic network topologies [3]. VANETs have captured considerable attention from both researchers and the vehicular community. This type of network falls under the mobile ad hoc network (MANET)category, where vehicles are treated as communication nodes [4]. These vehicles employ transceivers to enable technologies, such as advanced driver-assistance systems (ADAS), the Internet of Things (IoT), and communication modes like vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and vehicle-to-anything (V2X) [5; 6; 7; 8]. The technology adheres to the IEEE 802.11p standards, facilitating the WAVE and DSRC models [6; 9; 10]. In this setup, vehicles collaborate using MANETs, resulting in dynamic and fast-paced communication that introduces significant challenges to the network structure. Consequently, the quality of service (QoS), including communication reliability, scalability, and quality, suffers. Various protocols have been proposed to alleviate the impact of poor inter-vehicular communication. However, achieving cooperation among deployed vehicular nodes remains complex. Intelligent clustering protocols have emerged to enhance network QoS substantially. Routing protocols in ad hoc networks include non-clustering routing protocols and clustering routing protocols. Non-clustering routing protocols are based on a flat or peer-to-peer network structure and proactive (table-driven) or reactive (on-demand) route discovery mechanisms. Clustering routing protocols involve division of the network into smaller, manageable clusters, logically grouping vehicular nodes based on factors like communication links and node distances [6]. Clustering helps improve scalability by reducing the number of nodes participating in routing, which minimizes control overhead. Moreover, cluster heads can intelligently manage traffic within clusters, leading to better load balancing and improved network efficiency. In cluster protocols, control messages are confined to within clusters, reducing the overall control overhead in the network. In addition, clustering can provide better security and isolation within clusters, making it harder for external attackers to disrupt the network [11]. Clustering ant colony optimization (ACO) in VANETs is a technique used to address various optimization problems related to clustering in VANETs. Fuzzy logic and artificial bee colony (ABC) optimization can be applied to routing protocols in various ways to optimize the routing process in ad hoc networks. Fuzzy logic can be used to make routing decisions based on imprecise or uncertain network information considering factors like signal strength, link quality, and node mobility to make intelligent routing decisions.