To keep the services and applications of Intelligent Transportation System (ITS) stable and active, Vehicular Ad hoc Networks (VANETs) are considered as an essential building block to maintain and manage its features. A wide deployment of VANETs is possible only after addressing numerous research challenges. One of the most complicated issues consists in designing a routing strategy, taking into consideration several serious constraints, and especially in a network such as VANET. The severity of these issues would be increased significantly when a VANET is deployed over an urban area, where we distinguish the high mobility of nodes and existing obstructions (e.g., buildings, bridges, tunnels, etc.). In this paper, an efficient routing solution based on a flooding technique is conceived to make the data delivery more reliable and to guarantee robust paths. Vehicles can cooperate in ad hoc fashion with existing Unmanned Aerial Vehicles (UAVs). This kind of collaboration provides reliable routing paths and ensures alternative solutions in the case of path failures. Furthermore, a prediction technique is used to expect the expiration time of each discovered path. To limit the overhead over the network, all control packets are characterized by their static size making the originality of this work. Based on the simulation outputs, we discuss the performances of the proposed approach as compared with other dedicated previous schemes in terms of several metrics. The obtained results demonstrate that the hybrid communication between vehicles and UAVs based on the proposed flooding technique is perfectly suited to improve the data delivery process.

Summary Much progress can be expected in the domain of unmanned aerial vehicle (UAV) communication by the next decade. The cooperation between multiple UAVs in the air exchanging data among themselves can naturally form a flying ad hoc network (FANET). Such networks can be the key support to accomplish several kinds of missions while providing the required assistance to terrestrial networks. However, they are confronted with many challenges and difficulties, which are due to the high mobility of UAVs, the frequent packet losses, and the weak links between UAVs, all affecting the reliability of the data delivery. Furthermore, the unbalanced energy consumption may result in earlier UAV failure and consequently accelerate the decrease of the network lifetime, thus disrupting the overall network. This paper supports the use of the movement information and the residual energy level of each UAV to guarantee a high level of communication stability while predicting a sudden link breakage prior to its occurrence. A robust route discovery process is used to explore routing paths where the balanced energy consumption, the link breakage prediction, and the connectivity degree of the discovered paths are all considered. The performance of the scheme is evaluated through a series of simulations. The outcomes demonstrate the benefits of the proposed scheme in terms of increasing the lifetime of the network, minimizing the number of path failures, and decreasing the packet losses.

When it comes to keeping the data routing robust and effective in vehicular ad hoc networks (VANETs), stable and durable connectivity constitutes the keystone to ensure successful point-to-point communication. Since VANETs can comprise all kinds of mobile vehicles moving and changing direction frequently, this may result in frequent link failures and network partitions. Moreover, when VANETs are deployed in a city environment, another problem arises, that is, the existing obstructions (eg, buildings, trees, and hoppers) preventing the line-of-sight between vehicles, thus degrading wireless transmissions. Therefore, it is more complicated to design a routing technique that adapts to frequent changes in the topology. In order to settle all these problems, in this work, we design a flooding scheme that automatically reacts at each topology variation while overcoming the present obstacles while exchanging data in ad hoc mode with drones that are commonly called unmanned aerial vehicles (UAVs). Also, the aim of this work is to explore well-regulated routing paths providing a long lifetime connectivity based on the amount of traffic and the expiration time of each discovered path. A set of experiments is carried out using a simulation, and the outcomes are confronted with similar protocols based on a couple of metrics.The results clearly show that the assistance of UAVs to vehicles is capable of providing high delivery ratios and low delivery delays while efficiently extending the network connectivity.

Routing data in Vehicular Ad hoc Networks is still a challenging topic. The unpredictable mobility of nodes renders routing of data packets over optimal paths not always possible. Therefore, there is a need to enhance the routing service. Bus Rapid Transit systems, consisting of buses characterized by a regular mobility pattern, can be a good candidate for building a backbone to tackle the problem of uncontrolled mobility of nodes and to select appropriate routing paths for data delivery. For this purpose, we propose a new routing scheme called Busbased Routing Technique (BRT) which exploits the periodic and predictable movement of buses to learn the required time (the temporal distance) for each data transmission to RoadSide Units (RSUs) through a dedicated bus-based backbone. Indeed, BRT comprises two phases: (i) Learning process which should be carried out, basically, one time to allow buses to build routing tables entries and expect the delay for routing data packets over buses, (ii) Data delivery process which exploits the prelearned temporal distances to route data packets through the bus backbone towards an RSU (backbone mode). BRT uses other types of vehicles to boost the routing of data packets and also provides a maintenance procedure to deal with unexpected situations like a missing nexthop bus, which allows BRT to continue routing data packets. Simulation results show that BRT provides good performance results in terms of delivery ratio and end-to-end delay.

Vehicular ad hoc networks (VANETs) are characterized by frequent routing path failures due to the high mobility caused by the sudden changes of the direction of vehicles. The routing paths between two different vehicles should be established with this challenge in mind. Stability and connectedness are a mandatory condition to ensure a robust and reliable data delivery. The idea behind this work is to exploit a new reactive routing technique to provide regulated and well-connected routing paths. Unmanned Aerial Vehicles (UAVs) or what are referred to as drones can be both involved in the discovery process and be full members in these discovered paths in order to avoid possible disconnections on the ground when the network is sparsely connected. The different tests of this technique are performed based on NS-2 simulator and the outcomes are compared with those of related on-demand routing protocols dedicated for VANETs. Interesting results are distinguished showing a reduced end-to-end delay and a high delivery ratio, which proving that this heterogeneous communication between vehicles and UAVs is able to extend the network connectivity.

With the ever‐expanding rise of network demands and user expectations, the fifth generation (5G) of cellular networks was envisioned to support a plethora of use cases and conflicting user demands. Next to providing traditional connectivity like its previous generations, 5G also promises to be a heterogeneous network connecting humans, vehicles, unmanned aerial vehicles (UAVs), smart devices, and more. These challenging expectations proved to be overwhelming for traditional network infrastructures to handle. Network slicing has emerged as a promising solution that can achieve such diverse, taxing, and sometimes conflicting requirements in a dynamic and programmable way. There is no denying that UAVs have attained significant focus and research in recent years, and with 5G already being deployed, UAVs can now exploit the capabilities of the new networks. Extensive research is being taken to integrate UAVs into networks, assisting and improving aspects like latency, coverage, and capacity. Motivated by these facts, this survey distinguishes itself from other works by jointly exploring 5G, network slicing, and UAVs. The main contributions of this article are to showcase how UAVs can assist networks, provide a taxonomy of UAVs in the context of network slicing, and survey works that contribute to network slicing with UAVs. In this article, we present a comprehensive survey on UAVs in the context of network slicing, covering contributions, and state‐of‐the‐art literature. We discuss network slicing in‐depth, focusing especially on the three major slices: enhanced Mobile BroadBand, massive machine type communications, and ultra‐reliable low‐latency communications. We provide an overview of 5G enablers, including software‐defined networking and network function virtualization. We cover UAVs and identify their roles in networks as both users and assistants. Furthermore, this survey provides insight into open issues and future research directions related to network slicing and UAVs before concluding.

Secure routing protocols that are based only on cryptographic techniques cannot guarantee security against all attacks. Among solutions that have been proposed to enhance the security in vehicular networks are the distributed revocation protocols, which provide vehicles with the ability to quickly detect and avoid malicious attacks. However, most of the proposed revocation protocols are vulnerable to colluding attacks conducted by malicious nodes, a situation which results in denial of service. In this work, we propose a new and robust distributed revocation protocol for vehicular ad hoc networks, called Secure Distributed Revocation Protocol (SDRP), with the main objective to exclude misbehaving nodes conducting or not a colluding attack from the routing operation in VANET. We present an evaluation analysis of SDRP on the basis of the simulation results and show that our scheme provides a high detection rate of misbehaving nodes with a low rate of false positives even in the presence of a large number of attackers. Copyright © 2012 John Wiley & Sons, Ltd.

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