Simulating Opportunistic Networks: Survey and Future Directions

(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works[EN] Simulation is one of the most powerful tools we have for evaluating the performance of opportunistic networks (OppNets). In this paper, we focus on available tools and mod- els, compare their performance and precision and experimentally show the scalability of different simulators. We also perform a gap analysis of state-of-the-art OppNet simulations and sketch out possible further development and lines of research. This paper is targeted at students starting work and research in this area while also serving as a valuable source of information for experienced researchers.This work was supported in part by the Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, in part by the Universidad Laica Eloy Alfaro de Manabi, and in part by the Secretaria Nacional de Educacion Superior, Ciencia, Tecnologia e Innovacion, Ecuador. (Corresponding author: Jens Dede.)Dede, J.; Förster, A.; Hernández-Orallo, E.; Herrera-Tapia, J.; Kuladinithi, K.; Kuppusamy, V.; Manzoni, P.... (2018). Simulating Opportunistic Networks: Survey and Future Directions. IEEE Communications Surveys & Tutorials. 20(2):1547-1573. https://doi.org/10.1109/COMST.2017.2782182S1547157320

Improving Message Dissemination in Opportunistic Networks

Data transmission has become a need in various fields, like in social networks with the diverse interaction applications, or in the scientific and engineering areas where for example the use of sensors to capture data is growing, or in emergency situations where there is the imperative need to have a communication system to coordinate rescue operations. Wireless networks have been able to solve these issues to a great extent, but what can we do when a fixed supporting infrastructure is not available or becomes inoperative because of saturation? Opportunistic wireless networks are an alternative to consider in these situations, since their operation does not depend on the existence of a telecommunications infrastructure but they provide connectivity through the organized cooperation of users. This research thesis focuses on these types of networks and is aimed at improving the dissemination of information in opportunistic networks analyzing the main causes that influence the performance of data transmission. Opportunistic networks do not depend on a fixed topology but depend on the number and mobility of users, the type and quantity of information generated and sent, as well as the physical characteristics of the mobile devices that users have to transmit the data. The combination of these elements impacts on the duration of the contact time between mobile users, directly affecting the information delivery probability. This thesis starts by presenting a thorough "state of the art" study where we present the most important contributions related to this area and the solutions offered for the evaluation of the opportunistic networks, such as simulation models, routing protocols, simulation tools, among others. After offering this broad background, we evaluate the consumption of the resources of the mobile devices that affect the performance of the the applications of opportunistic networks, both from the energetic and the memory point of view. Next, we analyze the performance of opportunistic networks considering either pedestrian and vehicular environments. The studied approaches include the use of additional fixed nodes and different data transmission technologies, to improve the duration of the contact between mobile devices. Finally, we propose a diffusion scheme to improve the performance of data transmission based on extending the duration of the contact time and the likelihood that users will collaborate in this process. This approach is complemented by the efficient management of the resources of the mobile devices.La transmisión de datos se ha convertido en una necesidad en diversos ámbitos, como en las redes sociales con sus diversas aplicaciones, o en las áreas científicas y de ingeniería donde, por ejemplo, el uso de sensores para capturar datos está creciendo, o en situaciones de emergencia donde impera la necesidad de tener un sistema de comunicación para coordinar las operaciones de rescate. Las redes inalámbricas actuales han sido capaces de resolver estos problemas en gran medida, pero ¿qué podemos hacer cuando una infraestructura de soporte fija no está disponible o estas se vuelven inoperantes debido a la saturación de peticiones de red? Las redes inalámbricas oportunísticas son una alternativa a considerar en estas situaciones, ya que su funcionamiento no depende de la existencia de una infraestructura de telecomunicaciones sino que la conectividad es a través de la cooperación organizada de los usuarios. Esta tesis de investigación se centra en estos tipos de redes oportunísticas y tiene como objetivo mejorar la difusión de información analizando las principales causas que influyen en el rendimiento de la transmisión de datos. Las redes oportunísticas no dependen de una topología fija, sino que dependen del número y la movilidad de los usuarios, del tipo y cantidad de información generada y enviada, así como de las características físicas de los dispositivos móviles que los usuarios tienen para transmitir los datos. La combinación de estos elementos influye en la duración del tiempo de contacto entre usuarios móviles, afectando directamente a la probabilidad de entrega de información. Esta tesis comienza presentando un exhaustivo estudio del ``estado del arte", donde presentamos las contribuciones más importantes relacionadas con esta área y las soluciones existentes para la evaluación de las redes oportunísticas, tales como modelos de simulación, protocolos de enrutamiento, herramientas de simulación, entre otros. Tras ofrecer esta amplia compilación de investigaciones, se evalúa el consumo de recursos de los dispositivos móviles que afectan al rendimiento de las aplicaciones de redes oportunísticas, desde el punto de vista energético así como de la memoria. A continuación, analizamos el rendimiento de las redes oportunísticas considerando tanto los entornos peatonales como vehiculares. Los enfoques estudiados incluyen el uso de nodos fijos adicionales y diferentes tecnologías de transmisión de datos, para mejorar la duración del contacto entre dispositivos móviles. Finalmente, proponemos un esquema de difusión para mejorar el rendimiento de la transmisión de datos basado en la extensión de la duración del tiempo de contacto, y de la probabilidad de que los usuarios colaboren en este proceso. Este enfoque se complementa con la gestión eficiente de los recursos de los dispositivos móviles.La transmissió de dades s'ha convertit en una necessitat en diversos àmbits, com ara en les xarxes socials amb les diverses aplicacions d'interacció, o en les àrees científiques i d'enginyeria, en les quals, per exemple, l'ús de sensors per a capturar dades creix en l'actualitat, o en situacions d'emergència en què impera la necessitat de tenir un sistema de comunicació per a coordinar les operacions de rescat. Les xarxes sense fil han sigut capaces de resoldre aquests problemes en gran manera, però què podem fer quan una infraestructura de suport fixa no està disponible, o bé aquestes es tornen inoperants a causa de la saturació de peticions de xarxa? Les xarxes sense fil oportunistes són una alternativa que cal considerar en aquestes situacions, ja que el funcionament d'aquestes xarxes no depèn de l'existència d'una infraestructura de telecomunicacions, sinó que la connectivitat s'hi aconsegueix a través de la cooperació organitzada dels usuaris. Aquesta tesi de recerca se centra en aquest tipus de xarxes, i té com a objectiu millorar la difusió d'informació en xarxes oportunistes tot analitzant les principals causes que influeixen en el rendiment de la transmissió de dades. Les xarxes oportunistes no depenen d'una topologia fixa, sinó del nombre i la mobilitat dels usuaris, del tipus i la quantitat d'informació generada i enviada, i de les característiques físiques dels dispositius mòbils que els usuaris tenen per a transmetre les dades. La combinació d'aquests elements influeix en la durada del temps de contacte entre usuaris mòbils, i afecta directament la probabilitat de lliurament d'informació. Aquesta tesi comença amb un estudi exhaustiu de l'estat de la qüestió, en què presentem les contribucions més importants relacionades amb aquesta àrea i les solucions oferides per a l'avaluació de les xarxes oportunistes, com ara models de simulació, protocols d'encaminament o eines de simulació, entre d'altres. Després de mostrar aquest ampli panorama, s'avalua el consum dels recursos dels dispositius mòbils que afecten l'acompliment de les aplicacions de xarxes oportunistes, tant des del punt de vista energètic com de la memòria. A continuació, analitzem l'acompliment de xarxes oportunistes considerant tant els entorns de vianants com els vehiculars. Els enfocaments estudiats inclouen l'ús de nodes fixos addicionals i diferents tecnologies de transmissió de dades per a millorar la durada del contacte entre dispositius mòbils. Finalment, proposem un esquema de difusió per a millorar el rendiment de la transmissió de dades basat en l'extensió de la durada del temps de contacte, i de la probabilitat que els usuaris col·laboren en aquest procés. Aquest enfocament es complementa amb la gestió eficient dels recursos dels dispositius mòbils.Herrera Tapia, J. (2017). Improving Message Dissemination in Opportunistic Networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86129TESI

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics

Named Data Networking in Vehicular Ad hoc Networks: State-of-the-Art and Challenges

International audienceInformation-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community

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

H3N - Analysewerkzeuge für hybride Wegewahl in heterogenen, unterbrechungstoleranten Ad-Hoc-Netzen für Rettungskräfte

Rettungskräfte müssen unter widrigen Bedingungen zuverlässig kommunizieren können, um in Rettungseinsätzen effizient arbeiten zu können und somit Leben zu retten. Idealerweise ist dazu ein selbstorganisiertes Ad-Hoc-Netz notwendig, weil die Kommunikationsinfrastruktur ggf. beschädigt oder überlastet sein kann. Um die geforderte Robustheit der Kommunikation auch in Szenarien mit größeren zu überbrückenden Entfernungen zu gewährleisten, werden zusätzlich Mechanismen benötigt, die eine Unterbrechungstoleranz ermöglichen. Verzögerungstolerante Netze (engl. Delay Tolerant Networks, kurz: DTN) stellen solche Mechanismen bereit, erfordern aber zusätzliche Verzögerungen, die für Rettungskommunikation nachteilig sind. Deshalb werden intelligente hybride Wegewahlverfahren benötigt, um die Verzögerung durch DTN-Mechanismen zu begrenzen. Außerdem sollten entsprechende Verfahren heterogene Netze unterstützen. Das ermöglicht zusätzlich eine effizientere Weiterleitung durch die Nutzung von Geräten mit unterschiedlichen Kommunikationstechnologien und damit auch Reichweiten. Um solche Systeme und die dafür benötigten Kommunikationsprotokolle zu entwickeln, werden verschiedene Analysewerkzeuge genutzt. Dazu gehören analytische Modelle, Simulationen und Experimente auf der Zielsystemhardware. Für jede Kategorie gibt es verschiedene Werkzeuge und Frameworks, die sich auf unterschiedliche Aspekte fokussieren. Dadurch unterstützen diese herkömmlichen Analysemethoden jedoch meistens nur einen der oben genannten Punkte, während die Untersuchung von hybriden und/oder heterogenen Ansätzen und Szenarien nicht ohne weiteres möglich ist. Im Falle von Rettungskräften kommt hinzu, dass die charakteristischen Merkmale hinsichtlich der Bewegung der Knoten und des erzeugten Datenverkehrs während eines Einsatzes ebenfalls nicht modelliert werden können. In dieser Arbeit werden deshalb verschiedene Erweiterungen zu existierenden Analysewerkzeugen sowie neue Werkzeuge zur Analyse und Modelle zur Nachbildung realistischer Rettungsmissionen untersucht und entwickelt. Ziel ist es, die Vorteile existierender Werkzeuge miteinander zu kombinieren, um ganzheitliche, realitätsnahe Untersuchungen von hybriden Protokollen für heterogene Netze zu ermöglichen. Die Kombination erfolgt in Form von gezielten Erweiterungen und der Entwicklung ergänzender komplementärer Werkzeuge unter Verwendung existierender Schnittstellen. Erste Ergebnisse unter Verwendung der entwickelten Werkzeuge zeigen Verbesserungspotentiale bei der Verwendung traditioneller Protokolle und erlauben die Bewertung zusätzlicher Maßnahmen, um die Kommunikation zu verbessern. Szenarien zur Kommunikation von Rettungskräften werden dabei als ein Beispiel verwendet, die Tools sind jedoch nicht auf die Analyse dieses Anwendungsfalls beschränkt. Über die reine Analyse verschiedener existierender Ansätze hinaus bildet die entwickelte Evaluationsumgebung eine Grundlage für die Entwicklung und Verifikation von neuartigen hybriden Protokollen für die entsprechenden Systeme.Communication between participating first responders is essential for efficient coordination of rescue missions and thus allowing to save human lives. Ideally, ad hoc-style communication networks are applied to this as the first responders cannot rely on infrastructure-based communication for two reasons. First, the infrastructure could be damaged by the disastrous event or not be available for economic reasons. Second, even if public infrastructure is available and functional, it might be overloaded by users. To guarantee the robustness and reliability requirements of first responders, the Mobile Ad Hoc Networks (MANETs) have to be combined with an approach to mitigate intermittent connectivity due to otherwise limited connectivity. Delay Tolerant Networks (DTNs) provide such a functionality but introduce additional delay which is problematic. Therefore, intelligent hybrid routing approaches are required to limit the delay introduced by DTN mechanisms. Besides that, the approach should be applicable to heterogeneous networks in terms of communication technologies and device capabilities. This is required for cross multi-agency and volunteer communication but also enables the opportunistic exploitation of any given communication option. To evaluate such systems and develop the corresponding communication protocols, various tools for the analysis are available. This includes analytical models, simulations and real-world experiments on target hardware. In each category a wide set of tools is available already. However, each tool is focused on specific aspects usually and thus does not provide methods to analyze hybrid approaches out of the box. Even if the tools are modular and allow an extension, there are often other tools that are better suited for partial aspects of hybrid systems. In addition to this, few tools exist to model the characteristics of first responder networks. Especially the generalized movement during missions and the generated data traffic are difficult to model and integrate into analyses. The focus of this project is therefore to develop selected extensions to existing analysis and simulation tools as well as additional tools and models to realistically capture the characteristics of first responder networks. The goal is to combine the advantages of existing specialized simulation tools to enable thorough evaluations of hybrid protocols for heterogeneous networks based on realistic assumptions. To achieve this, the tools are extended by specifically designing tools that enable the interaction between tools and new tools that complement the existing analysis capabilities. First results obtained via the resulting toolbox clearly indicate further research directions as well as a potential for protocol enhancements. Besides that, the toolbox was used to evaluate various methods to enhance the connectivity between nodes in first responder networks. First responder scenarios are used as an example here. The toolbox itself is however not limited to this use case. In addition to the analysis of existing approaches for hybrid and heterogeneous networks, the developed toolbox provides a base framework for the development and verification of newly developed protocols for such use cases

Optimized acquisition of spatially distributed phenomena in public sensing systems

Nowadays, an increasing number of popular consumer electronics is shipped with a variety of sensors. The usage of these as a wireless sensing platform, where users are the key architectural component, and ubiquitous access to communication infrastructure has established a new application area called public sensing. We present an opportunistic public sensing system that allows for a flexible and efficient acquisition of sensor readings. This work considers the usage of smartphones as a sensor network in a model-driven sensor data acquisition. We focus on efficiency of query dissemination to mobile nodes, while retaining high effectiveness regarding defined sensing quality of collected data. We adopted and extended an existing geographic routing protocol to design an efficient com- munication system that executes model-driven data acquisition and is robust to changing sensors availability. We use in-network processing paradigm to efficiently distribute queries to mobile nodes and to collect results afterwards. The developed approach was simulated using OMNeT++ network simulator. To verify implemented algorithms and test the overall system performance, we run simulations in different scenarios and evaluate them using adequate cov- erage metrics. Moreover, we verify our intuitive extension to adopted routing protocol and show that it can have a strong impact on the efficiency of protocol in question

Journal of Telecommunications and Information Technology, 2014, nr 3

kwartalni

Swarming Reconnaissance Using Unmanned Aerial Vehicles in a Parallel Discrete Event Simulation

Current military affairs indicate that future military warfare requires safer, more accurate, and more fault-tolerant weapons systems. Unmanned Aerial Vehicles (UAV) are one answer to this military requirement. Technology in the UAV arena is moving toward smaller and more capable systems and is becoming available at a fraction of the cost. Exploiting the advances in these miniaturized flying vehicles is the aim of this research. How are the UAVs employed for the future military? The concept of operations for a micro-UAV system is adopted from nature from the appearance of flocking birds, movement of a school of fish, and swarming bees among others. All of these natural phenomena have a common thread: a global action resulting from many small individual actions. This emergent behavior is the aggregate result of many simple interactions occurring within the flock, school, or swarm. In a similar manner, a more robust weapon system uses emergent behavior resulting in no weakest link because the system itself is made up of simple interactions by hundreds or thousands of homogeneous UAVs. The global system in this research is referred to as a swarm. Losing one or a few individual unmanned vehicles would not dramatically impact the swarms ability to complete the mission or cause harm to any human operator. Swarming reconnaissance is the emergent behavior of swarms to perform a reconnaissance operation. An in-depth look at the design of a reconnaissance swarming mission is studied. A taxonomy of passive reconnaissance applications is developed to address feasibility. Evaluation of algorithms for swarm movement, communication, sensor input/analysis, targeting, and network topology result in priorities of each model\u27s desired features. After a thorough selection process of available implementations, a subset of those models are integrated and built upon resulting in a simulation that explores the innovations of swarming UAVs

Towards addressing training data scarcity challenge in emerging radio access networks: a survey and framework

The future of cellular networks is contingent on artificial intelligence (AI) based automation, particularly for radio access network (RAN) operation, optimization, and troubleshooting. To achieve such zero-touch automation, a myriad of AI-based solutions are being proposed in literature to leverage AI for modeling and optimizing network behavior to achieve the zero-touch automation goal. However, to work reliably, AI based automation, requires a deluge of training data. Consequently, the success of the proposed AI solutions is limited by a fundamental challenge faced by cellular network research community: scarcity of the training data. In this paper, we present an extensive review of classic and emerging techniques to address this challenge. We first identify the common data types in RAN and their known use-cases. We then present a taxonomized survey of techniques used in literature to address training data scarcity for various data types. This is followed by a framework to address the training data scarcity. The proposed framework builds on available information and combination of techniques including interpolation, domain-knowledge based, generative adversarial neural networks, transfer learning, autoencoders, fewshot learning, simulators and testbeds. Potential new techniques to enrich scarce data in cellular networks are also proposed, such as by matrix completion theory, and domain knowledge-based techniques leveraging different types of network geometries and network parameters. In addition, an overview of state-of-the art simulators and testbeds is also presented to make readers aware of current and emerging platforms to access real data in order to overcome the data scarcity challenge. The extensive survey of training data scarcity addressing techniques combined with proposed framework to select a suitable technique for given type of data, can assist researchers and network operators in choosing the appropriate methods to overcome the data scarcity challenge in leveraging AI to radio access network automation