Abstract
Owing to the explosive expansion of wireless communication and networking technologies, cost-effective unmanned aerial vehicles (UAVs) have recently emerged and soon they will occupy the major part of our sky. UAVs can be exploited to efficiently accomplish complex missions when cooperatively organized as an ad hoc network, thus creating the well-known flying ad hoc networks (FANETs). The establishment of such networks is not feasible without deploying an efficient networking model allowing a reliable exchange of information between UAVs. FANET inherits common features and characteristics from mobile ad hoc networks (MANETs) and their sub-classes, such as vehicular ad hoc networks (VANETs) and wireless sensor networks (WSNs). Unfortunately, UAVs are often deployed in the sky adopting a mobility model dictated by the nature of missions that they are expected to handle, and therefore, differentiate themselves from any traditional networks. Moreover, several flying constraints and the highly dynamic topology of FANETs make the design of routing protocols a complicated task. In this paper, a comprehensive survey is presented covering the architecture, the constraints, the mobility models, the routing techniques, and the simulation tools dedicated to FANETs. A classification, descriptions, and comparative studies of an important number of existing routing protocols dedicated to FANETs are detailed. Furthermore, the paper depicts future challenge perspectives, helping scientific researchers to discover some themes that have been addressed only ostensibly in the literature and need more investigation. The novelty of this survey is its uniqueness to provide a complete analysis of the major FANET routing protocols and to critically compare them according to different constraints based on crucial parameters, thus better presenting the state of the art of this specific area of research.
Highlights
With more and more Unmanned Aerial Vehicles (UAVs) flying over our heads, there is an ever-increasing need for coordination, communication, safety, and information sharing among these devices in order to be a practical choice for various applications including search and rescue, patrolling, delivery of goods, and military [1]
Based on a novel and original taxonomy, we present a comprehensive survey of the majority of routing protocols applied or exclusively developed to flying ad hoc networks (FANETs) and classified based on nine categories: (i) Topology-based, (ii) Secure-based, (iii) Swarm-based, (iv) Hierarchical-based, (v) Energybased, (vi) Heterogeneous-based, (vii) Position-based, FIGURE 2
We provide a global comparative analysis of the discussed FANET routing protocols, which allows us to have an overview of the adopted routing strategies, the different requirements, the features, and the type of experimental validation to be used
Summary
With more and more Unmanned Aerial Vehicles (UAVs) flying over our heads, there is an ever-increasing need for coordination, communication, safety, and information sharing among these devices in order to be a practical choice for various applications including search and rescue, patrolling, delivery of goods, and military [1]. In the case when a UAV finds a pheromone in its neighborhood, it selects its direction based on a probability defined beforehand (c.f., Figure 9(a)) This model can be used in different search and rescue applications using UAVs. H3MP (Hybrid Markov Mobility Model with Pheromones) [144] is a combination of DPR and Markov models exploiting the advantages of both in a specified area decomposed of zones. SDPC (Self-Deployable Point Coverage) [145] is a topology-based mobility model dedicated to FANETs. SDPC can be applied to enhance the coverage of a maximum of mobile nodes located on the ground while maintaining connectivity among UAVs. To do so, an optimal positioning of UAVs has to be considered to cover the largest possible area (c.f., Figure 9(c)). A comparison between the main features that are considered as the key components differentiating between the mobility models, such as the randomness that defines the degree of random motion used in each mobility model, the collision avoidance, the connectivity that is defined as the distance separating the UAVs, and the deployment area
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