117 research outputs found

    Design and Performance Analysis of a Geographic Routing Protocol for Highly Dynamic MANETs

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    Efficient multi-hop routing has become important for airborne telemetry networks. The highly dynamic nature in these scenarios results in short-lived links. Geographic-based routing has an advantage over topology-based routing to make rapid forwarding decisions based on neighbor and destination position. The AeroRP geographic routing protocol is detailed, which uses a heuristic metric for forwarding decisions that takes transmission range and a neighbor's location and velocity into consideration. The main contributions of this work include detailing and finalizing the routing decision metrics, design, and simulation implementation of AeroRP. The analysis of the simulations shows AeroRP has several advantages over other MANET routing protocols and offers tradeoffs for different performance metrics in the form of different AeroRP modes. Specifically, AeroRP yields higher accuracy than all compared routing protocols and various AeroRP modes can be chosen depending on how packet delivery and delay are prioritized

    Managing Congestion in Vehicular Networks Using Tabu Search

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    © 2018, Springer Nature Switzerland AG. In this era of communication, exponentially growing networks bring a lot of challenges to address for smoother network functionalities. Among them is efficiency in handling packet traffic to avoid and control congestion. A particular case is applicable to Vehicular Ad-hoc Networks, which are known with unbalanced resource utilisation, communication overheads, high transmission delay and least transmission capacity. This paper aims to minimise the delay and jitter for enhancing the Quality of Service (QoS) in Vehicular Adhoc Networks (VANET) using tabu search algorithm with multi-channel allocation capability. We proposed a scheme that prioritises each message considering the basis of message type or its substances, such as crisis, reference point, and administration oriented etc., and uses tabu search for scheduling the transmission of queued messages in order to enhance the efficiency, security, and durability of VANET. A comprehensive simulation is conducted to validate the proposed scheme and to evaluate the performances in comparison with other state-of-the-art approaches

    Benchmarking Wireless Network Protocols: Threat and Challenge Analysis of the AeroRP

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    To accommodate the unique conditions of mobile wireless networks, numerous protocols have been designed. Protocols are initially tested through simulation software, but often under non-realistic conditions, using simple or even ideal wireless environments not usually found in the real world. Without challenges and channel impairments, such simulations cannot accurately determine the advantages and disadvantages of the protocol nor can a reliable comparison be made between the performance of any two protocols. New protocols must be tested in a manner consistent with legacy protocols so they can be accurately compared and improved upon. The contributions of this thesis are a set of models that can create more realistic and challenging simulations, including a 3-D implementation of the Gauss-Markov mobility model, and a set of benchmarks that can be used to test the strengths and weaknesses of wireless routing protocols. These benchmarks are then applied to several MANET protocols including AODV, DSR, OLSR, DSDV, and AeroRP that is part of the Aero protocol stack developed at The University of Kansas. AeroRP outperforms the traditional MANET routing protocols in benchmarks that involve either highly-dynamic networks or disruptions in connectivity

    Mission-based mobility models for UAV networks

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    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

    Data Gathering and Dissemination over Flying Ad-hoc Networks in Smart Environments

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    The advent of the Internet of Things (IoT) has laid the foundations for new possibilities in our life. The ability to communicate with any electronic device has become a fascinating opportunity. Particularly interesting are UAVs (Unmanned Airborne Vehicles), autonomous or remotely controlled flying devices able to operate in many contexts thanks to their mobility, sensors, and communication capabilities. Recently, the use of UAVs has become an important asset in many critical and common scenarios; thereby, various research groups have started to consider UAVs’ potentiality applied on smart environments. UAVs can communicate with each other forming a Flying Ad-hoc Network (FANET), in order to provide complex services that requires the coordination of several UAVs; yet, this also generates challenging communication issues. This dissertation starts from this standpoint, firstly focusing on networking issues and potential solutions already present in the state-of-the-art. To this aim, the peculiar issues of routing in mobile, 3D shaped ad-hoc networks have been investigated through a set of simulations to compare different ad-hoc routing protocols and understand their limits. From this knowledge, our work takes into consideration the differences between classic MANETs and FANETs, highlighting the specific communication performance of UAVs and their specific mobility models. Based on these assumptions, we propose refinements and improvements of routing protocols, as well as their linkage with actual UAV-based applications to support smart services. Particular consideration is devoted to Delay/Disruption Tolerant Networks (DTNs), characterized by long packet delays and intermittent connectivity, a critical aspect when UAVs are involved. The goal is to leverage on context-aware strategies in order to design more efficient routing solutions. The outcome of this work includes the design and analysis of new routing protocols supporting efficient UAVs’ communication with heterogeneous smart objects in smart environments. Finally, we discuss about how the presence of UAV swarms may affect the perception of population, providing a critical analysis of how the consideration of these aspects could change a FANET communication infrastructure

    The Internet of Everything

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    In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)
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