RECAST: Telling Apart Social and Random Relationships in Dynamic Networks

International audienceIn this paper, we argue that the ability to accurately spot random and social relationships in dynamic networks is essential to net- work applications that rely on human routines, such as, e.g., op- portunistic routing. We thus propose a strategy to analyze users' interactions in mobile networks where users act according to their interests and activity dynamics. Our strategy, named Random rElationship ClASsifier sTrategy (RECAST), allows classifying users' wireless interactions, separating random interactions from differ- ent kinds of social ties. To that end, RECAST observes how the real system differs from an equivalent one where entities' decisions are completely random. We evaluate the effectiveness of the RECAST classification on real-world user contact datasets collected in diverse networking contexts. Our analysis unveils significant dif- ferences among the dynamics of users' wireless interactions in the datasets, which we leverage to unveil the impact of social ties on opportunistic routing

Performance evaluation of 5G access technologies and SDN transport network on an NS3 simulator

In this article, we deal with the enhanced Mobile Broadband (eMBB) service class, defined within the new 5G communication paradigm, to evaluate the impact of the transition from 4G to 5G access technology on the Radio Access Network and on the Transport Network. Simulation results are obtained with ns3 and performance analyses are focused on 6 GHz radio scenarios for the Radio Access Network, where an Non-Standalone 5G configuration has been assumed, and on SDN-based scenarios for the Transport Network. Inspired by the 5G Transformer model, we describe and simulate each single element of the three main functional plains of the proposed architecture to aim a preliminary evaluation of the end-to-end system performances

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

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

Adaptive Mechanisms to Improve Message Dissemination in Vehicular Networks

En el pasado, se han dedicado muchos recursos en construir mejores carreteras y autovías. Con el paso del tiempo, los objetivos fueron cambiando hacia las mejoras de los vehículos, consiguiendo cada vez vehículos más rápidos y con mayor autonomía. Más tarde, con la introducción de la electrónica en el mercado del automóvil, los vehículos fueron equipados con sensores, equipos de comunicaciones, y otros avances tecnológicos que han permitido la aparición de coches más eficientes, seguros y confortables. Las aplicaciones que nos permite el uso de las Redes Vehiculares (VNs) en términos de seguridad y eficiencia son múltiples, lo que justifica la cantidad y recursos de investigación que se están dedicando en los últimos años. En el desarrollo de esta Tesis, los esfuerzos se han centrado en el área de las Vehicular Ad-hoc Networks, una subclase de las Redes Vehiculares que se centra en las comunicaciones entre los vehículos, sin necesidad de que existan elementos de infraestructura. Con la intención de mejorar el proceso de diseminación de mensajes de alerta, imprescindibles para las aplicaciones relacionadas con la seguridad, se ha propuesto un esquema de difusión adaptativo, capaz de seleccionar automáticamente el mecanismo de difusión óptimo en función de la complejidad del mapa y de la densidad actual de vehículos. El principal objetivo es maximizar la efectividad en la difusión de mensajes, reduciendo al máximo el número de mensajes necesarios, evitando o mitigando las tormentas de difusión. Las propuestas actuales en el área de las VANETs, se centran principalmente en analizar escenarios con densidades típicas o promedio. Sin embargo, y debido a las características de este tipo de redes, a menudo se dan situaciones con densidades extremas (altas y bajas). Teniendo en cuenta los problemas que pueden ocasionar en el proceso de diseminación de los mensajes de emergencia, se han propuesto dos nuevos esquemas de difusión para bajas densidades: el \emph{Junction Store and Forward} (JSF) y el \emph{Neighbor Store and Forward} (NSF). Además, para situaciones de alta densidad de vehículos, se ha diseñado el \emph{Nearest Junction Located} (NJL), un esquema de diseminación que reduce notablemente el número de mensajes enviados, sin por ello perder prestaciones. Finalmente, hemos realizado una clasificacion de los esquemas de difusión para VANETs más importantes, analizando las características utilizadas en su diseño. Además hemos realizado una comparación de todos ellos, utilizando el mismo entorno de simulación y los mismos escenarios, permitiendo conocer cuál es el mejor esquema de diseminación a usar en cada momento

How Human Mobility Models Can Help to Deal with COVID-19

[EN] One of the key factors for the spreading of human infections, such as the COVID-19, is human mobility. There is a huge background of human mobility models developed with the aim of evaluating the performance of mobile computer networks, such as cellular networks, opportunistic networks, etc. In this paper, we propose the use of these models for evaluating the temporal and spatial risk of transmission of the COVID-19 disease. First, we study both pure synthetic model and simulated models based on pedestrian simulators, generated for real urban scenarios such as a square and a subway station. In order to evaluate the risk, two different risks of exposure are defined. The results show that we can obtain not only the temporal risk but also a heat map with the exposure risk in the evaluated scenario. This is particularly interesting for public spaces, where health authorities could make effective risk management plans to reduce the risk of transmission.Hernández-Orallo, E.; Armero-Martínez, A. (2021). How Human Mobility Models Can Help to Deal with COVID-19. Electronics. 10(1):1-24. https://doi.org/10.3390/electronics1001003312410

L'intertextualité dans les publications scientifiques

La base de données bibliographiques de l'IEEE contient un certain nombre de duplications avérées avec indication des originaux copiés. Ce corpus est utilisé pour tester une méthode d'attribution d'auteur. La combinaison de la distance intertextuelle avec la fenêtre glissante et diverses techniques de classification permet d'identifier ces duplications avec un risque d'erreur très faible. Cette expérience montre également que plusieurs facteurs brouillent l'identité de l'auteur scientifique, notamment des collectifs de chercheurs à géométrie variable et une forte dose d'intertextualité acceptée voire recherchée

Using topology and neighbor information to overcome adverse vehicle density conditions

Vehicular networks supporting cooperative driving on the road have attracted much attention due to the plethora of new possibilities they offer to modern Intelligent Transportation Systems. However, research works regarding vehicular networks usually obviate assessing their proposals in scenarios including adverse vehicle densities, i.e., density values that significantly differ from the average values, despite such densities can be quite common in real urban environments (e.g. traffic jams). In this paper, we study the effect of these hostile conditions on the performance of different schemes providing warning message dissemination. The goal of these schemes is to maximize message delivery effectiveness, something difficult to achieve in adverse density scenarios. In addition, we propose the Neighbor Store and Forward (NSF) scheme, designed to be used under low density conditions, and the Nearest Junction Located (NJL) scheme, specially developed for high density conditions. Simulation results demonstrate that our proposals are able to outperform existing warning message dissemination schemes in urban environments under adverse vehicle density conditions. In particular, NSF reduces the warning notification time in low vehicle density scenarios, while increasing up to 23.3% the percentage of informed vehicles. As for high vehicle density conditions, NJL is able to inform the same percentage of vehicles than other existing approaches, while reducing the number of messages up to 46.73%This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03-01, by the Fundacion Universitaria Antonio Gargallo and the Obra Social de Ibercaja, under Grant 2013/B010, as well as the Government of Aragon and the European Social Fund (T91 Research Group).Sanguesa, JA.; Fogue, M.; Garrido, P.; Martinez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM. (2014). Using topology and neighbor information to overcome adverse vehicle density conditions. Transportation Research Part C: Emerging Technologies. 42:1-13. https://doi.org/10.1016/j.trc.2014.02.010S1134