A survey on network simulators in three-dimensional wireless ad hoc and sensor networks

© 2016 The Author(s). As steady research in wireless ad hoc and sensor networks is going on, performance evaluation through relevant network simulator becomes indispensable procedure to demonstrate superiority to comparative schemes and suitability in most literatures. Thus, it is very important to establish credibility of simulation results by investigating merits and limitations of each simulator prior to selection. Based on this motivation, in this article, we present a comprehensive survey on current network simulators for new emerging research area, three-dimensional wireless ad hoc and sensor networks which is represented by airborne ad hoc networks and underwater sensor networks by reviewing major existing simulators as well as presenting their main features in several aspects. In addition, we address the outstanding mobility models which are main components in simulation study for self-organizing ad hoc networks. Finally, open research issues and research challenges are discussed and presented

Performance Assessment of a New Routing Protocol in AANET

Routing is a critical issue in mobile ad hoc networks. The routing algorithm must take into account the specific properties of the network such as its topology, the mobility of the nodes and their number. In this paper, we present a simulation-based study of the performances of our innovative routing protocol named NoDe-TBR (Node Density TBR) that takes into account the actual node density distribution. The considered ad hoc network is an Aeronautical Ad hoc NETwork (AANET), a future communication system enabling air↔air and air↔ground communications beyond the radio range of the sender. This context and the communication architecture have been modeled in a realistic way based on replayed aircraft trajectories, a realistic access layer, and application that should be deployed in the future

Aeronautical Ad Hoc Network for Civil Aviation

Aeronautical communication systems are constantly evolving in order to handle the always increasing flow of data generated by civil aviation. In this article we first present communication systems currently used for en-route aircraft. We then propose Aeronautical Ad hoc NETwork (AANET) as a complementary communication system and demonstrate its connectivity and assess the throughput by simulations based on real aircraft trajectories over the French sky and over the Atlantic ocean

High-Throughput Air-to-Ground Connectivity for Aircraft

Permanent connectivity to the Internet has become the defacto standard in the second decade of the 21st century. However, on-board aircraft connectivity is still limited. While the number of airlines offering in-flight connectivity increases, the current performance is insufficient to satisfy several hundreds of passengers simultaneously. There are several options to connect aircraft to the ground, i.e. direct air-to-ground, satellites and relaying via air-to-air links. However, each single solution is insufficient. The direct air-to-ground coverage is limited to the continent and coastal regions, while the satellite links are limited in the minimum size of the spot beams and air-to-air links need to be combined with a link to the ground. Moreover, even if a direct air-to-ground or satellite link is available, the peak throughput offered on each link is rarely achieved, as the capacity needs to be shared with other aircraft flying in the same coverage area. The main challenge in achieving a high throughput per aircraft lies in the throughput allocation. All aircraft should receive a fair share of the available throughput. More specifically, as an aircraft contains a network itself, a weighted share according to the aircraft size should be provided. To address this problem, an integrated air-to-ground network, which is able to provide a high throughput to aircraft, is proposed here. Therefore, this work introduces a weighted-fair throughput allocation scheme to provide such a desired allocation. While various aspects of aircraft connectivity are studied in literature, this work is the first to address an integrated air-to-ground network to provide high-throughput connectivity to aircraft. This work models the problem of throughput allocation as a mixed integer linear program. Two throughput allocation schemes are proposed, a centralized optimal solution and a distributed heuristic solution. For the optimal solution, two different objectives are introduced, a max-min-based and a threshold-based objective. The optimal solution is utilized as a benchmark for the achievable throughput for small scenarios, while the heuristic solution offers a distributed approach and can process scenarios with a higher number of aircraft. Additionally, an option for weighted-fair throughput allocation is included. Hence, large aircraft obtain a larger share of the throughput than smaller ones. This leads to fair throughput allocation with respect to the size of the aircraft. To analyze the performance of throughput allocation in the air-to-ground network, this work introduces an air-to-ground network model. It models the network realistically, but independent from specific network implementations, such as 5G or WiFi. It is also adaptable to different scenarios. The aircraft network is studied based on captured flight traces. Extensive and representative parameter studies are conducted, including, among others, different link setups, geographic scenarios, aircraft capabilities, link distances and link capacities. The results show that the throughput can be distributed optimally during high-aircraft-density times using the optimal solution and close to optimal using the heuristic solution. The mean throughput during these times in the optimal reference scenario with low Earth orbit satellites is 20 Mbps via direct air-to-ground links and 4 Mbps via satellite links, which corresponds to 10.7% and 1.9% of the maximum link throughput, respectively. Nevertheless, during low-aircraft-density times, which are less challenging, the throughput can reach more than 200 Mbps. Therefore, the challenge is on providing a high throughput during high-aircraft-density times. In the larger central European scenario, using the heuristic scheme, a minimum of 22.9 Mbps, i.e. 3.2% of the maximum capacity, can be provided to all aircraft during high-aircraft-density times. Moreover, the critical parameters to obtain a high throughput are presented. For instance, this work shows that multi-hop air-to-air links are dispensable for aircraft within direct air-to-ground coverage. While the computation time of the optimal solution limits the number of aircraft in the scenario, larger scenarios can be studied using the heuristic scheme. The results using the weighted-fair throughput allocation show that the introduction of weights enables a user-fair throughput allocation instead of an aircraft-fair throughput allocation. As a conclusion, using the air-to-ground model and the two introduced throughput allocation schemes, the achievable weighted-fair throughput per aircraft and the respective link choices can be quantified

Multiple-Objective Packet Routing Optimization for Aeronautical ad-hoc Networks

Providing Internet service above the clouds is of ever-increasing interest and in this context aeronautical ad-hoc networking (AANET) constitutes a promising solution. However, the optimization of packet routing in large ad hoc networks is quite challenging. In this paper, we develop a discrete ε multiobjective genetic algorithm (ε-DMOGA) for jointly optimizing the end-to-end latency, the end-to-end spectral efficiency (SE), and the path expiration time (PET) that specifies how long the routing path can be relied on without re-optimizing the path. More specifically, a distance-based adaptive coding and modulation (ACM) scheme specifically designed for aeronautical communications is exploited for quantifying each link’s achievable SE. Furthermore, the queueing delay at each node is also incorporated into the multiple-objective optimization metric. Our ε-DMOGA assisted multiple-objective routing optimization is validated by real historical flight data collected over the Australian airspace on two selected representative dates

Routage basé sur le contenu dans les réseaux ad-hoc aéronautiques

In a context of growing needs of communication means to increase flight safety and meet the expectations of companies and passengers, the world of civil aviation seeks new communication systems that can meet these objectives. The Aeronautical Ad-Hoc Networks, AANETs represent an innovative approach to address this problem. It is self-configured networks, using no fixed infrastructure where the nodes are commercial aircraft. The AANETs can be seen as a subset of the VANET (Vehicular Ad-Hoc Networks) since they share many features as the constraints imposed on the trajectories. In order to use these mobile networks more efficiently while meeting the needs of new applications, such as the transmission of weather information in real time, requiring air to air communications. , we propose in this thesis to use the paradigm of content based routing above AANET. In this kind of routing, it is not a destination address that is used to identify the recipients, but the message content itself. In this paradigm, a transmitter sends a message having attributes and the message is then transmitted by the network to nodes interested by the content of the message. Applied to weather information update, this approach allows an aircraft detecting a dangerous phenomenon such as a thunderstorm to only prevent interested nodes, ie those whose the trajectory come close to the storm during the lifetime of the event. In this thesis, we have chosen to rely on the popular Publish / Subscribe (P / S) paradigm to provide a content based routing service. In this approach, publishers publish events. On the other side, nodes send subscriptions to declare their interest and the system is then in charge of forward events to nodes that match their needs.. After a state of the art about existing P / S systems, particularly those adapted to VANETs, we choose to test the solutions seemed interesting in a AANET context. To accomplish this, we have developed as a Omnet ++ mobility model using real position reports to replay a full day of traffic of aircraft and several aeronautical applications based on a P / S system to generate realistic data. The results show that these solutions are not completely suitable for AANET context. Therefore, in a second step, we proposed a new P / S system which is more efficient on a AANET. This solution is based on an overlay network built thanks to a new of 1-hopping clustering algorithm suitable for AANET. In order to increase the stability of the overlay architecture, this algorithm is based on the number of neighbors and the relative mobility between the nodes to define groups. The tests show that the P iii / S system based on this overlay provides better results than the previously tested solutions, whether in terms of network load or percentage of transmitted events.Les réseaux Ad Hoc mobiles (MANET : Mobile Ad hoc NETworks), sont des réseaux auto-configurés, n'utilisant pas d'infrastructure fixe. Les AANET (Aeronautical Ad hoc NETworks) sont un sous-ensemble de ces réseaux dont la spécificité réside dans le fait que les nœuds composant le réseau sont des avions commerciaux avec des schémas de mouvements caractéristiques. Les AANETs peuvent apparaître comme un moyen de communication complémentaire aux systèmes existants entre les avions et le sol ou entre les avions eux mêmes. Afin de répondre aux besoins de nouvelles applications, telle que l'information météorologique sur des phénomènes dangereux en temps réel, qui nécessitent des communications d'avion à avion, le paradigme du routage basé sur le contenu semble prometteur. Dans ce type de routage, ce n'est plus une adresse de destination qui est utilisée pour joindre le ou les correspondants, mais le contenu du message qui permet de décider des destinataires. Dans ce paradigme, un émetteur envoi un message possédant des attributs et le message est alors transmis par le réseau uniquement aux terminaux intéressés par le contenu du message. Dans cette thèse, nous avons conçu un système de publication/souscription basé sur le contenu et adapté aux AANETs. Ce système s'appuie sur une architecture recouvrante ("overlay network") construite à l'aide d'un algorithme original de regroupement à 1-saut (1-hop clusterisation) adapté aux AANETs. Ce système a été validé en simulation avec un rejeu de trajectoires avion réelles

Semi-Stochastic Aircraft Mobility Modelling for Aeronautical Networks: An Australian Case-Study Based on Real Flight Data

Terrestrial Internet access is gradually becoming the norm across the globe. However, there is a growing demand for Internet access of passenger airplanes. Hence, it is essential to develop aeronautical networks above the clouds. Therefore the conception of an aircraft mobility model is one of the prerequisite for aeronautical network design and optimization. However, there is a paucity of realistic aircraft mobility models capable of generating large-scale flight data. To fill this knowledge-gap, we develop a semi-stochastic aircraft mobility model based on large-scale real historical Australian flights acquired both on June 29th, 2018 and December 25th, 2018, which represent the busiest day and the quietest day of 2018, respectively. The semi-stochastic aircraft mobility model is capable of generating an arbitrary number of flights, which can emulate the specific features of aircraft mobility. The semi-stochastic aircraft mobility model was then analysed and validated both by the physical layer performance and network layer performance in the case study of Australian aeronautical networks, demonstrating that it is capable of reflecting the statistical characteristics of the real historical flights

Mission-based mobility models for UAV networks

Las redes UAV han atraído la atención de los investigadores durante la última década. Las numerosas posibilidades que ofrecen los sistemas single-UAV aumentan considerablemente al usar múltiples UAV. Sin embargo, el gran potencial del sistema multi-UAV viene con un precio: la complejidad de controlar todos los aspectos necesarios para garantizar que los UAVs cumplen la misión que se les ha asignado. Ha habido numerosas investigaciones dedicadas a los sistemas multi-UAV en el campo de la robótica en las cuales se han utilizado grupos de UAVs para diferentes aplicaciones. Sin embargo, los aspectos relacionados con la red que forman estos sistemas han comenzado a reclamar un lugar entre la comunidad de investigación y han hecho que las redes de UAVs se consideren como un nuevo paradigma entre las redes multi-salto. La investigación de redes de UAVs, de manera similar a otras redes multi-salto, se divide principalmente en dos categorías: i) modelos de movilidad que capturan la movilidad de la red, y ii) algoritmos de enrutamiento. Ambas categorías han heredado muchos algoritmos que pertenecían a las redes MANET, que fueron el primer paradigma de redes multi-salto que atrajo la atención de los investigadores. Aunque hay esfuerzos de investigación en curso que proponen soluciones para ambas categorías, el número de modelos de movilidad y algoritmos de enrutamiento específicos para redes UAV es limitado. Además, en el caso de los modelos de movilidad, las soluciones existentes propuestas son simplistas y apenas representan la movilidad real de un equipo de UAVs, los cuales se utilizan principalmente en operaciones orientadas a misiones, en la que cada UAV tiene asignados movimientos específicos. Esta tesis propone dos modelos de movilidad basados en misiones para una red de UAVs que realiza dos operaciones diferentes. El escenario elegido en el que se desarrollan las misiones corresponde con una región en la que ha ocurrido, por ejemplo, un desastre natural. La elección de este tipo de escenario se debe a que en zonas de desastre, la infraestructura de comunicaciones comúnmente está dañada o totalmente destruida. En este tipo de situaciones, una red de UAVs ofrece la posibilidad de desplegar rápidamente una red de comunicaciones. El primer modelo de movilidad, llamado dPSO-U, ha sido diseñado para capturar la movilidad de una red UAV en una misión con dos objetivos principales: i) explorar el área del escenario para descubrir las ubicaciones de los nodos terrestres, y ii) hacer que los UAVs converjan de manera autónoma a los grupos en los que se organizan los nodos terrestres (también conocidos como clusters). El modelo de movilidad dPSO-U se basa en el conocido algoritmo particle swarm optimization (PSO), considerando los UAV como las partículas del algoritmo, y también utilizando el concepto de valores dinámicos para la inercia, el local best y el neighbour best de manera que el modelo de movilidad tenga ambas capacidades: la de exploración y la de convergencia. El segundo modelo, denominado modelo de movilidad Jaccard-based, captura la movilidad de una red UAV que tiene asignada la misión de proporcionar servicios de comunicación inalámbrica en un escenario de mediano tamaño. En este modelo de movilidad se ha utilizado una combinación del virtual forces algorithm (VFA), de la distancia Jaccard entre cada par de UAVs y metaheurísticas como hill climbing y simulated annealing, para cumplir los dos objetivos de la misión: i) maximizar el número de nodos terrestres (víctimas) que se encuentran bajo el área de cobertura inalámbrica de la red UAV, y ii) mantener la red UAV como una red conectada, es decir, evitando las desconexiones entre UAV. Se han realizado simulaciones exhaustivas con herramientas software específicamente desarrolladas para los modelos de movilidad propuestos. También se ha definido un conjunto de métricas para cada modelo de movilidad. Estas métricas se han utilizado para validar la capacidad de los modelos de movilidad propuestos de emular los movimientos de una red UAV en cada misión.UAV networks have attracted the attention of the research community in the last decade. The numerous capabilities of single-UAV systems increase considerably by using multiple UAVs. The great potential of a multi-UAV system comes with a price though: the complexity of controlling all the aspects required to guarantee that the UAV team accomplish the mission that it has been assigned. There have been numerous research works devoted to multi-UAV systems in the field of robotics using UAV teams for different applications. However, the networking aspects of multi-UAV systems started to claim a place among the research community and have made UAV networks to be considered as a new paradigm among the multihop ad hoc networks. UAV networks research, in a similar manner to other multihop ad hoc networks, is mainly divided into two categories: i) mobility models that capture the network mobility, and ii) routing algorithms. Both categories have inherited previous algorithms mechanisms that originally belong to MANETs, being these the first multihop networking paradigm attracting the attention of researchers. Although there are ongoing research efforts proposing solutions for the aforementioned categories, the number of UAV networks-specific mobility models and routing algorithms is limited. In addition, in the case of the mobility models, the existing solutions proposed are simplistic and barely represent the real mobility of a UAV team, which are mainly used in missions-oriented operations. This thesis proposes two mission-based mobility models for a UAV network carrying out two different operations over a disaster-like scenario. The reason for selecting a disaster scenario is because, usually, the common communication infrastructure is malfunctioning or completely destroyed. In these cases, a UAV network allows building a support communication network which is rapidly deployed. The first mobility model, called dPSO-U, has been designed for capturing the mobility of a UAV network in a mission with two main objectives: i) exploring the scenario area for discovering the location of ground nodes, and ii) making the UAVs to autonomously converge to the groups in which the nodes are organized (also referred to as clusters). The dPSO-U mobility model is based on the well-known particle swarm optimization algorithm (PSO), considering the UAVs as the particles of the algorithm, and also using the concept of dynamic inertia, local best and neighbour best weights so the mobility model can have both abilities: exploration and convergence. The second one, called Jaccard-based mobility model, captures the mobility of a UAV network that has been assigned with the mission of providing wireless communication services in a medium-scale scenario. A combination of the virtual forces algorithm (VFA), the Jaccard distance between each pair of UAVs and metaheuristics such as hill climbing or simulated annealing have been used in this mobility model in order to meet the two mission objectives: i) to maximize the number of ground nodes (i.e. victims) under the UAV network wireless coverage area, and ii) to maintain the UAV network as a connected network, i.e. avoiding UAV disconnections. Extensive simulations have been performed with software tools that have been specifically developed for the proposed mobility models. Also, a set of metrics have been defined and measured for each mobility model. These metrics have been used for validating the ability of the proposed mobility models to emulate the movements of a UAV network in each mission