One of the most important design problems for multi-UAV (Unmanned Air Vehicle) systems is the communication which is crucial for cooperation and collaboration between the UAVs. If all UAVs are directly connected to an infrastructure, such as a ground base or a satellite, the communication between UAVs can be realized through the in-frastructure. However, this infrastructure based communication architecture restricts the capabilities of the multi-UAV systems. Ad-hoc networking between UAVs can solve the problems arising from a fully infrastructure based UAV networks. In this paper, Flying Ad-Hoc Networks (FANETs) are surveyed which is an ad hoc network connecting the UAVs. The differences between FANETs, MANETs (Mobile Ad-hoc Networks) and VANETs (Vehicle Ad-Hoc Networks) are clarified first, and then the main FANET design challenges are introduced. Along with the existing FANET protocols, open research issues are also discussed.

Flying Ad-Hoc Networks (FANETs)

Recently, unmanned aerial vehicles (UAVs), or drones, have attracted a lot of attention, since they represent a new potential market. Along with the maturity of the technology and relevant regulations, a worldwide deployment of these UAVs is expected. Thanks to the high mobility of drones, they can be used to provide a lot of applications, such as service delivery, pollution mitigation, farming, and in the rescue operations. Due to its ubiquitous usability, the UAV will play an important role in the Internet of Things (IoT) vision, and it may become the main key enabler of this vision. While these UAVs would be deployed for specific objectives (e.g., service delivery), they can be, at the same time, used to offer new IoT value-added services when they are equipped with suitable and remotely controllable machine type communications (MTCs) devices (i.e., sensors, cameras, and actuators). However, deploying UAVs for the envisioned purposes cannot be done before overcoming the relevant challenging issues. These challenges comprise not only technical issues, such as physical collision, but also regulation issues as this nascent technology could be associated with problems like breaking the privacy of people or even use it for illegal operations like drug smuggling. Providing the communication to UAVs is another challenging issue facing the deployment of this technology. In this paper, a comprehensive survey on the UAVs and the related issues will be introduced. In addition, our envisioned UAV-based architecture for the delivery of UAV-based value-added IoT services from the sky will be introduced, and the relevant key challenges and requirements will be presented.

Low-Altitude Unmanned Aerial Vehicles-Based Internet of Things Services: Comprehensive Survey and Future Perspectives

Coverage path planning consists of finding the route which covers every point of a certain area of interest. In recent times, Unmanned Aerial Vehicles (UAVs) have been employed in several application domains involving terrain coverage, such as surveillance, smart farming, photogrammetry, disaster management, civil security, and wildfire tracking, among others. This paper aims to explore and analyze the existing studies in the literature related to the different approaches employed in coverage path planning problems, especially those using UAVs. We address simple geometric flight patterns and more complex grid-based solutions considering full and partial information about the area of interest. The surveyed coverage approaches are classified according to a classical taxonomy, such as no decomposition, exact cellular decomposition, and approximate cellular decomposition. This review also contemplates different shapes of the area of interest, such as rectangular, concave and convex polygons. The performance metrics usually applied to evaluate the success of the coverage missions are also presented.

Survey on Coverage Path Planning with Unmanned Aerial Vehicles

A survey on position-based routing protocols for Flying Ad hoc Networks (FANETs)

In most swarm systems, agents are either aware of the position of their direct neighbors or they possess a substrate on which they can deposit information (stigmergy). However, such resources are not always obtainable in real-world applications because of hardware and environmental constraints. In this paper we study in 2D simulation the design of a swarm system which does not make use of positioning information or stigmergy.

This endeavor is motivated by an application whereby a large number of Swarming Micro Air Vehicles (SMAVs), of fixed-wing configuration, must organize autonomously to establish a wireless communication network (SMAVNET) between users located on ground. Rather than relative or absolute positioning, agents must rely only on their own heading measurements and local communication with neighbors.

Designing local interactions responsible for the emergence of the SMAVNET deployment and maintenance is a challenging task. For this reason, artificial evolution is used to automatically develop neuronal controllers for the swarm of homogenous agents. This approach has the advantage of yielding original and efficient swarming strategies. A detailed behavioral analysis is then performed on the fittest swarm to gain insight as to the behavior of the individual agents.

Evolved swarming without positioning information: an application in aerial communication relay

In MANET research the mobility of the nodes is often described using standard synthetic models. Given a particular application, e.g. networks of unmanned aerial vehicles (UAVs) performing a cooperative task, the use of a standard synthetic mobility model can result in incorrect conclusions, as the movement pattern can impact the networking performance of the system. In this paper we present the criteria that characterize desirable mobility properties for the movement of UAVs in a reconnaissance scenario, and provide two mobility models for the scenario. In the first mobility model the UAVs move independently and randomly, and in the second model pheromones guide their movement. The random model is very simple but it achieves mediocre results. The pheromone model has very good scanning properties, but it has problems with respect to network connectivity. The study shows that there in an inherent conflict between the two goals of maximum coverage by frequent rescanning and adequate communication connectivity.

/pdf/mobility-models-for-uav-group-reconnaissance-applications-1q5hvywku6.pdf

Mobility Models for UAV Group Reconnaissance Applications

A major tool used for evaluating routing protocols in ad hoc and delay-tolerant networks is simulation. Whereas the results from simulations give good insights, they are limited to the specific scenario set-up that is used. If the scenario changes, new and often time-consuming simulations have to be run. Moreover, the simulation time in packet-level simulators with fairly realistic physical layer implementation, such as ns-2, generally grows rapidly in the number of nodes. This practically limits the number of nodes in a simulation, even if the limit can be extended by the use of simulation federations. Larger scenarios can also be facilitated by the use of more abstraction in the physical layer; abstractions that may impact the validity of the results. In this article, we present the forward-wait framework--a mathematical model describing the packet movements for opportunistic geographic delay-tolerant routing protocols. By describing packet movements as a sequence of alternating forwarding and waiting phases, the framework can accurately predict the routing performance. Key input parameters to the framework are random variables describing the forwarding and waiting phases. We show how the properties of the random variables can be derived, both via abstract modeling and small scale ns-2 simulation data. The model is then used to demonstrate the prediction capabilities of the framework in providing results that are close to the (much slower) packet-level simulations.

/pdf/a-framework-for-performance-analysis-of-geographic-delay-4yf6h55a7x.pdf

A framework for performance analysis of geographic delay-tolerant routing

Performing large scale physical experiments to evaluate the packet delivery ratio, latency, and resource utilization in mobile ad hoc networks is a costly and difficult exercise. A more cost-effective method of performing trade-off studies in connection with protocol evaluations is simulation. However, simulations are often time consuming and require a detailed description of a given scenario's mobility and topology. A more general approach for scalability and performance studies is the use of abstract models of behavior in networks of mobile nodes. This paper illustrates the power of such a model by illustrating the prediction capability of the Forward-Wait framework with respect to the routing performance of geographic delay-tolerant routing. The Forward-Wait mathematical framework describes packet movements as a sequence of alternating forwarding and waiting phases. Key input parameters to the Forward-Wait framework are distributions describing the forwarding and waiting phases, and the source destination distance. The paper shows how these distributions can be derived and used to predict the routing performance in different scenarios and a variety of network sizes.

/pdf/predicting-the-performance-of-geographic-delay-tolerant-1de091eia6.pdf

Erik Kuiper

Papers

Mobility Models for UAV Group Reconnaissance Applications

A framework for performance analysis of geographic delay-tolerant routing

Predicting the performance of geographic delay-tolerant routing