On Mass-Spring System Implementation in Cluster-Based MANETs for Natural Disaster Applications

Communication after natural disasters is paramount.Disasters such as earthquakes, hurricanes and tsunamis leavethe affected area reachable only to wireless devices. In suchconditions, Mobile Ad-hoc Networks (MANETs) play a criticalrole. The issue of MANETs communication backbone can beaddressed by self-organized cluster-based algorithms. The vir-tual backbone will maintain an efficient communication on theMANET, adapting to the dynamic topology changes thanks toits self-organized nature. Nevertheless, they do not take intoaccount the node’s mobility. If a node moves away from itsneighboring nodes, connectivity will be lost and thus, networksegmentation will occur. Therefore, it is fundamental to maintainthe connectivity and the communication between nodes whileexploring the area. In this paper, we propose the applicationof a mass-spring system on the Energy-Efficient Self-OrganizedAlgorithm (EESOA) for Disaster Area applications. Results willshow that our proposal performs best when deployment ofMANET’s nodes is dense while maintaining a connected network.ITESO, A.C

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Effects of Data Replication on Data Exfiltration in Mobile Ad hoc Networks Utilizing Reactive Protocols

A swarm of autonomous UAVs can provide a significant amount of ISR data where current UAV assets may not be feasible or practical. As such, the availability of the data the resides in the swarm is a topic that will benefit from further investigation. This thesis examines the impact of le replication and swarm characteristics such as node mobility, swarm size, and churn rate on data availability utilizing reactive protocols. This document examines the most prominent factors affecting the networking of nodes in a MANET. Factors include network routing protocols and peer-to-peer le protocols. It compares and contrasts several open source network simulator environments. Experiment implementation is documented, covering design considerations, assumptions, and software implementation, as well as detailing constant, response and variable factors. Collected data is presented and the results show that in swarms of sizes of 30, 45, and 60 nodes, le replication improves data availability until network saturation is reached, with the most significant benefit gained after only one copy is made. Mobility, churn rate, and swarm density all influence the replication impact

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

Unmanned Aerial Vehicle for Internet of Everything: Opportunities and Challenges

The recent advances in information and communication technology (ICT) have further extended Internet of Things (IoT) from the sole "things" aspect to the omnipotent role of "intelligent connection of things". Meanwhile, the concept of internet of everything (IoE) is presented as such an omnipotent extension of IoT. However, the IoE realization meets critical challenges including the restricted network coverage and the limited resource of existing network technologies. Recently, Unmanned Aerial Vehicles (UAVs) have attracted significant attentions attributed to their high mobility, low cost, and flexible deployment. Thus, UAVs may potentially overcome the challenges of IoE. This article presents a comprehensive survey on opportunities and challenges of UAV-enabled IoE. We first present three critical expectations of IoE: 1) scalability requiring a scalable network architecture with ubiquitous coverage, 2) intelligence requiring a global computing plane enabling intelligent things, 3) diversity requiring provisions of diverse applications. Thereafter, we review the enabling technologies to achieve these expectations and discuss four intrinsic constraints of IoE (i.e., coverage constraint, battery constraint, computing constraint, and security issues). We then present an overview of UAVs. We next discuss the opportunities brought by UAV to IoE. Additionally, we introduce a UAV-enabled IoE (Ue-IoE) solution by exploiting UAVs's mobility, in which we show that Ue-IoE can greatly enhance the scalability, intelligence and diversity of IoE. Finally, we outline the future directions in Ue-IoE.Comment: 21 pages, 9 figure

Design of an UAV swarm

This master thesis tries to give an overview on the general aspects involved in the design of an UAV swarm. UAV swarms are continuoulsy gaining popularity amongst researchers and UAV manufacturers, since they allow greater success rates in task accomplishing with reduced times. Appart from this, multiple UAVs cooperating between them opens a new field of missions that can only be carried in this way. All the topics explained within this master thesis will explain all the agents involved in the design of an UAV swarm, from the communication protocols between them, navigation and trajectory analysis and task allocation

Formation coordination and network management of UAV networks using particle swarm optimization and software-defined networking

In recent years, with the growth in the use of Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. The lack of reliable communication infrastructure in these scenarios has motivated the use of UAVs to establish a network as flying nodes, also known as UAV networks. However, the high mobility degree of flying and terrestrial users may be responsible for constant changes in nodes’ positioning, which makes it more challenging to guarantee their communication during the operational time. In this context, this work presents a framework solution for formation coordination and network management of UAVs, which aims to establish and maintain a set of relays units in order to provide a constant, reliable and efficient communication link among user nodes - which are performing individual or collaborative missions on its turn. Such a framework relies on a set of formation coordination algorithms - including the Particle Swarm Optimization (PSO) evolutionary algorithm -, and also considers the use of Software-defined Networking-based (SDN) communication protocol for network management. For coordination proposes, a novel particle selection criteria is proposed, which aims to guarantee network manageability of UAV formations, therefore being able to guarantee service persistence in case of nodes’ failure occurrence, as well as to provide required network performance, as a consequence. Simulations performed in OMNeT++ show the efficiency of the proposed solution and prove a promising direction of the solution for accomplishing its purposes.Em regiões de confrontos militares, em cenários pós-catástrofes naturais e, inclusive, em grandes áreas de cultivo agrícola, é comum a ausência de uma infra-estrutura préestabelecida de comunicação entre usuários durante a execução de uma ou mais operações eventuais. Nestes casos, Veículos Aéreos Não Tripulados (VANTs) podem ser vistos como uma alternativa para o estabelecimento de uma rede temporária durante essas missões. Para algumas aplicações, a alta mobilidade destes usuários podem trazem grandes desafios para o gerenciamento autônomo de uma estrutura de comunicação aérea, como a organização espacial dos nós roteadores e as políticas de encaminhamento de pacotes adotadas durante a operação. Tendo isso em vista, esse trabalho apresenta o estudo de uma solução que visa o estabelecimento e manutenção das conexões entre os usuários - nos quais executam tarefas individuais ou colaborativas -, através do uso de algoritmos de coordenação de formação - no qual inclui o algoritmo evolucionário Otimização por Enxame de Partículas -, e, também, de conceitos relacionados a Rede Definidas por Software para o gerenciamento da rede. Ainda, é proposto um novo critério de seleção das partículas do algoritmo evolucionário, visando garantir gerenciabilidade das topologias formadas e, consequentemente, a persistência do serviço em caso de falha dos nós roteadores, assim como o cumprimento de especificações desejadas para o desempenho da rede. Simulações em OMNeT++ mostraram a eficácia da proposta e sustentam o modelo proposto a fim de atingir seus objetivos