VLDB 2026 Research / reviewers in the wild / expert
Francisco J. Martinez
dblp:27/8016 · also Francisco José Martínez Domínguez
· DBLP profile ↗
41ranked-venue papers
5as first author
8since 2021 · last 2025
0000-0001-6945-7330ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 22 · 4 first-author · 5 since 2021Artificial intelligence and machine learning · 7 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 3 · 1 since 2021Systems, architecture and hardware · 2Human-computer interaction and ubiquitous computing · 1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | FresSim: A Coverage Simulator for LoRaWAN Based on Fresnel ZoneabstractThis article introduces the LoRaWAN Fresnel Zone Simulator (FresSim), a tool designed to evaluate the feasibility of LoRaWAN deployments by analyzing the Fresnel Zone and terrain topography, allowing for the early prediction of coverage between nodes and the gateway. Furthermore, unlike other tools, FresSim can integrate real data from platforms such as The Things Network (TTN) and ChirpStack, providing an accurate assessment of potential coverage and signal quality in real deployments. Comparisons between FresSim and LoRaSim, a widely used signal propagation simulator, reveal that FresSim offers superior accuracy in scenarios with complex topography, achieving a 100% success rate in predicting coverage, doubling the 50% accuracy rate of LoRaSim. These results demonstrate that FresSim is a valuable tool for optimizing LoRaWAN networks in open environments, significantly contributing to the improvement of LoRaWAN deployment planning. Vicente Torres-Sanz, Pablo Donate, Julio A. Sanguesa, Piedad Garrido, Francisco J. Martinez |
LCN | 5 |
| 2025 | SecureAutoLoRa: An Automated Secure Registration Procedure for LoRaWAN DevicesabstractDevice registration in LoRaWAN systems can be a tedious process, particularly when managing a large number of devices. To automate this task, we previously developed the AutoLoraConfig protocol, although it includes vulnerabilities that attackers can exploit. To solve this, in this work we introduce the SecureAutoLoRa, a protocol designed to enhance security in the automated device registration process for LoRaWAN networks. SecureAutoLoRa blocks abuse of the guest DevEUI used in automated joins by obfuscating registration messages and enforcing a configurable positional security code that dictates where the real DevEUI appears across packets, markedly hindering unauthorized registrations.Results show that SecureAutoLoRa sharply reduces attackers’ success. Compared with AES-128 and SPECK, it complements standard encryption to provide a practical, layered defense suitable for large-scale LoRaWAN onboarding. Lucas Mallen, Julio A. Sanguesa, José Roldán Gómez, Vicente Torres-Sanz, Francisco J. Martinez |
MSWiM | 5 |
| 2025 | Predicting Home EV Charging Practices Using Machine LearningabstractThe rapid adoption of electric vehicles (EVs) demands advanced residential charging solutions, where user behavior varies widely due to factors like electricity tariffs and weather conditions. Such conditions make charging predictions particularly complex. This study addresses this challenge by predicting the time an EV remains connected to a residential charger using a dataset of 106,260 sessions. To this end, we propose the Connection Time Neural Model (CTNM), a deep neural network designed to model the complex dynamics of domestic charging, and we introduce the Weighted Error Metric (WEM), a novel metric that penalizes overestimations and under-estimations differently to reflect their real-world impacts on both grid management and user experience. Utilizing bidirectional charger data, we focus solely on connection time, bypassing energy prediction. CTNM is benchmarked against state-of-the-art methods (i.e., Random Forest, Dense Neural Network, XGBoost, and Support Vector Regression) using Mean Absolute Error, Root Mean Squared Error, and WEM as performance metrics. Results demonstrate CTNM’s superiority, reducing average error by 18%, and weighted error by 31% compared to Random Forest, thanks to its deep architecture and integration of contextual features, like variable tariffs and weather. Pablo Donate, Julio A. Sanguesa, Piedad Garrido, Vicente Torres-Sanz, Francisco J. Martinez, Carlos T. Calafate |
VTC2025-Fall | 5 |
| 2025 | Large language models accurately identify immunosuppression in intensive care unit patientsabstractOBJECTIVE: Rule-based structured data algorithms and natural language processing (NLP) approaches applied to unstructured clinical notes have limited accuracy and poor generalizability for identifying immunosuppression. Large language models (LLMs) may effectively identify patients with heterogenous types of immunosuppression from unstructured clinical notes. We compared the performance of LLMs applied to unstructured notes for identifying patients with immunosuppressive conditions or immunosuppressive medication use against 2 baselines: (1) structured data algorithms using diagnosis codes and medication orders and (2) NLP approaches applied to unstructured notes. MATERIALS AND METHODS: We used hospital admission notes from a primary cohort of 827 intensive care unit (ICU) patients at Northwestern Memorial Hospital and a validation cohort of 200 ICU patients at Beth Israel Deaconess Medical Center, along with diagnosis codes and medication orders from the primary cohort. We evaluated the performance of structured data algorithms, NLP approaches, and LLMs in identifying 7 immunosuppressive conditions and 6 immunosuppressive medications. RESULTS: In the primary cohort, structured data algorithms achieved peak F1 scores ranging from 0.30 to 0.97 for identifying immunosuppressive conditions and medications. NLP approaches achieved peak F1 scores ranging from 0 to 1. GPT-4o outperformed or matched structured data algorithms and NLP approaches across all conditions and medications, with F1 scores ranging from 0.51 to 1. GPT-4o also performed impressively in our validation cohort (F1 = 1 for 8/13 variables). DISCUSSION: LLMs, particularly GPT-4o, outperformed structured data algorithms and NLP approaches in identifying immunosuppressive conditions and medications with robust external validation. CONCLUSION: LLMs can be applied for improved cohort identification for research purposes. Vijeeth Guggilla, Mengjia Kang, Melissa J. Bak, Steven D. Tran, Anna Pawlowski, Prasanth Nannapaneni, Luke V. Rasmussen, Helen K. Donnelly, Ankit Agrawal 0001, David M. Liebovitz, Alexander V. Misharin, G. R. Scott Budinger, Richard G. Wunderink, Theresa Walunas, Catherine A. Gao, Alan R. Hauser, Alec Peltekian, Alexis Rose Wolfe, Alison L. Szabo, Alok N. Choudhary, Amy Ludwig, Anahid Amani Moghadam, Anjana V. Yeldandi, Ankit Bharat, Anna E. Pawlowski, Anthony M. Joudi, Arjun Prakash Tambe, Ashley J. Smith-Nunez, Benjamin D. Singer, Benjamin J. Ulrich, Betty Tran, Cara J. Gottardi, Chiagozie O. Pickens, Clara J. Schroedl, Daniel Meza, Dulce Sarai Garcia, Egon A. Ozer, Elen Gusman, Elisheva D. Shanes, Emily Mower Provost, Emily M. Olson, Erica Marie Hartmann, Erin A. Korth, Estefani Diaz, Estefany R. Guzman, Francisco J. Martinez, Gabrielle Matias, Hiam Abdala-Valencia, Jack T. Sumner, Jacob I Sznajder, Jacqueline M. Kruser, Jakub Glowala, James M. Walter, Jamie H. Rowell, Jason M. Arnold, John Coleman, Jon W. Lomasney, Joseph Isaac Bailey, Judd F. Hultquist, Justin A. Fiala, Justin Starren, Karen M. Ridge, Karolina Senkow, Kathryn A. Helmin, Khalilah L. Gates, Lacy Simmons, Lesley Pinzon, Lindsey D. Gradone, Lisa F. Wolfe, Lucy Luo, Luisa Morales-Nebreda, Manu Jain, Marc Sala, Maxwell Schleck, Melissa H. Ross, Melissa Querrey, Michael J. Cuttica, Michelle Hinsch Prickett, Nandita R. Nadig, Nathaniel Rhodes, Navdeep S. Chandel, Nikolay S. Markov, Peter H. S. Sporn, Qianli Liu, Rachel B. Kadar, Rachel L. Medernach, Ramon Lorenzo-Redondo, Ravi Kalhan, Rebecca K. Clepp, Richard I. Morimoto, Rogan A. Grant, Ruben J. Mylvaganam, Samuel Fenske, Scott A. Laurenzo, Seung Hye Han, Sophia Nozick, Srinivas Panchamukhi, Stephanie C. Eisenbarth, Suchitra Swaminathan, Susan R. Russell, Taylor A. Poor, Thaddeus Cybulski, Theresa A. Lombardo, Thomas Bolig, Thomas Stoeger, Tien Doan, Timothy Rowe, Wan-Ting Liao, Yuan Luo 0001, Yuliana Sokolenko, Ziyan Lu |
J. Am. Medical Informatics Assoc. | 48 |
| 2024 | AutoLoRaConfig: Automated Registration Procedure for LoRaWAN DevicesabstractLoRaWAN (Long Range Wide Area Network) is a communications protocol stack based on LoRa which provides long-range connectivity and low power consumption, making it a strong candidate for Internet of Things (IoT) device connectivity. However, unlike other technologies like WiFi or Bluetooth, LoRaWAN lacks an automatic mechanism to facilitate the connection of new devices to a network, which is undoubtedly a limitation for widespread device deployment. This paper presents AutoLoRaConfig, a rule-based system designed to automate the configuration and registration of devices in LoRaWAN networks, reducing the manual intervention required, and therefore minimizing potential human errors. The proposal aims to simplify the work required by users regarding the device configuration and registration process, enabling agile and efficient large-scale deployments. Results indicate that, for a set of 100 devices, automated deployment is 136.6 times faster than the manual procedure. Vicente Torres-Sanz, Julio A. Sanguesa, Francisco J. Martinez, Piedad Garrido, Carlos T. Calafate |
LCN | 3 |
| 2023 | aDBF: an autonomous electromagnetic noise filtering mechanism for industrial environmentsabstractThe use of proprietary systems in Industry 4.0 often involves high economic costs. To address this issue, using low-cost devices with similar capabilities is becoming an increasingly popular alternative. However, these devices are prone to suffer the negative effects of electromagnetic interference (EMI) due to their placement in electrical panels alongside other electromechanical devices. To solve this problem, this article presents the autonomous Data Base Filter (aDBF). aDBF is an enhanced electromagnetic interference filtering mechanism capable of eliminating erroneous signals generated by EMI. aDBF has been specifically designed to autonomously (i.e., without the need for operator supervision or intervention) determine both the number of different product types elaborated in a production line, and the time instants when their manufacturing process starts and ends. In particular, aDBF goes through three stages: (i) pre-filtering, (ii) product change detection, and (iii) identification of valid signals. The results obtained after validating our proposal in three different manufacturing shifts demonstrate that the aDBF filtering mechanism works very accurately, as the maximum error introduced is of 0.93%. Angel C. Herrero, Julio A. Sanguesa, Francisco J. Martinez, Piedad Garrido, Carlos T. Calafate |
ICCCN | 3 |
| 2023 | Analysis of the Influence of Terrain on LoRaWAN-based IoT DeploymentsabstractLong Range Wide Area Network (LoRaWAN) is a network protocol specifically designed to leverage the advantages of Long Range technology. LoRaWAN is employed to connect Internet of Things devices through a long-range network infrastructure, providing a secure and efficient communication layer that facilitates connectivity for a vast number of devices in a LoRa network. The aim of this study is to assess the real-life performance of LoRaWAN in different topographical environments. In particular, two scenarios (one flat and one mountainous) are compared, with an analysis of the success rate in data packet reception. The purpose is to examine how topography influences communication between LoRa devices and gateways, as well as to explore alternatives for overcoming challenges in rugged terrain environments. Therefore, in the mountainous environment, the study also investigates whether the use of drones could enhance communications. The findings of this study reveal that the topography of the terrain significantly impacts LoRa communications, resulting in a 58.63% decrease in the number of successfully received packets compared to a flat environment. Moreover, one-third of the nodes failed to establish communication with the ground gateway, and a partial improvement in connectivity was achieved by using gateways deployed on drones. Vicente Torres-Sanz, Julio A. Sanguesa, Félix Serna, Francisco J. Martinez, Piedad Garrido, Carlos T. Calafate |
MSWiM | 4 |
| 2022 | Neural Network-based Model for Traffic Prediction in the City of ValenciaabstractThere are many models that attempt to predict vehicular speed in urban and interurban roads, the noise pollution caused by traffic in cities, or even the traffic flow based on historical data from cameras or from people's mobile phones. Such information can be useful for administration authorities, and for researchers attempting to improve the living conditions of citizens. In this context, the aim of the present study is to design a model capable of predicting the traffic flow in the city of Valencia, Spain, based on data collected by electromagnetic loops distributed throughout the city. With a good traffic prediction, it will be possible to foresee possible traffic jams, and also to trigger countermeasures to mitigate them. Therefore, two models based on two recurrent neural networks of Long Short-Term Memory (LSTM) type have been designed to predict the traffic flow in the different streets of Valencia at the different hours of the day. We also study the influence of the specific characteristics used on the accuracy of the model. The results of our experiments show that, despite the high heterogeneity in terms of per-street traffic behaviour, it is possible to reach useful prediction models with low errors. Cristian Villarroya, Carlos T. Calafate, Eva Onaindia, Juan-Carlos Cano, Francisco J. Martinez |
KES | 5 |
| 2020 | Providing resilience to UAV swarms following planned missionsabstractAs we experience an unprecedented growth in the field of Unmanned Aerial Vehicles (UAVs), more and more applications keep arising due to the combination of low cost and flexibility provided by these flying devices, especially those of the multirrotor type. Within this field, solutions where several UAVs team-up to create a swarm are gaining momentum as they enable to perform more sophisticated tasks, or accelerate task execution compared to the single-UAV alternative. However, advanced solutions based on UAV swarms still lack significant advancements and validation in real environments to facilitate their adoption and deployment. In this paper we take a step ahead in this direction by proposing a solution that improves the resilience of swarm flights, focusing on handling the loss of the swarm leader, which is typically the most critical condition to be faced. Experiments using our UAV emulation tool (ArduSim) evidence the correctness of the protocol under adverse circumstances, and highlight that swarm members are able to seamlessly switch to an alternative leader when necessary, introducing a negligible delay in the process in most cases, while keeping this delay within a few seconds even in worst-case conditions. Jamie Wubben, Izan Catalán, Manel Lurbe, Francisco Fabra, Francisco J. Martinez, Carlos T. Calafate, Juan-Carlos Cano, Pietro Manzoni |
ICCCN | 5 |
| 2020 | An interference-resilient IIoT solution for measuring the effectiveness of industrial processesabstractThe development and deployment of the so-called Industrial Internet of Things (IIoT) have significantly increased the control and monitoring capabilities of companies, and thus their potential productivity. In this paper, we propose the use of Raspberry Pi devices in industrial environments to mea-sure productivity parameters. Our proposal can economically and efficiently gather data related with the availability and productivity of industrial machinery. However, since low-cost devices are prone to suffer the negative effects of electromagnetic interferences, we additionally propose an alternative to prevent signal alterations caused by them. More specifically, we propose a filtering mechanism called Smart Coded Filter (SCF), which eliminates wrong signals caused by electromagnetic interferences, and, therefore, highly improves the accuracy when estimating the availability metric. Results obtained demonstrate that our low-cost device provided with the SCF completely ignores 100% of wrong availability data, while reducing up to 70% the number of records stored into the database. Angel C. Herrero, Francisco J. Martinez, Piedad Garrido, Julio A. Sanguesa, Carlos T. Calafate |
IECON | 2 |
| 2019 | V-tracer: a Vehicular Trace Generator for Future Predictive MaintenanceabstractIn this paper we present V-tracer, a vehicular trace generator aimed at generating realistic data about mobility of vehicles, as well as their daily operation and wear. The objectives of our approach are two: first, gathering real traces obtained by in-vehicle on-board units (OBUs), and second, as the first target is hard to achieve, generating synthetic data. The final goal will be getting all the information that would be very useful to infer and predict vehicle failures. The traces provided by our generator may be used to perform the predictive maintenance of vehicles in the near future. Mirialys Machin, Piedad Garrido, Francisco J. Martinez, Julio A. Sanguesa |
CCNC | 3 |
| 2019 | Enhancing the NS-3 Simulator by Introducing Electric Vehicles FeaturesabstractElectric Vehicles (EVs) sales are increasing in the recent years due to several factors such as cost reduction, fuel cost increase, pollution reductions, government incentives, among others. At the same time, Intelligent Transportation Systems (ITS) are continuously improving, and researchers use different simulators in order to test their proposals before implementing them in real devices. However, traditional communications-aimed simulations do not include fuel consumption issues that are a key factor in transportation systems. This paper presents the addition of Electric Vehicles consumption to the ns-3 simulator, which currently is one of the most used network simulators. Our proposal follows all the models, coding style, as well as engineering guidelines of ns-3, coupled with the characteristics of each vehicle, to accurately estimate the energy consumption. We also analyze the performance of our proposal while simulating a part of the E313 highway, located in Antwerp, Belgium. In particular, we compare the ns-3 results obtained in terms of energy consumption to those obtained in SUMO. In addition, we study the impact of our proposal on the overall simulation time. Julio A. Sanguesa, Samuel Salvatella, Francisco J. Martinez, Johann Marquez-Barja, Manuel Ricardo 0001 |
ICCCN | 3 |
| 2017 | Dynamic Small Cell Management for Connected Cars CommunicationsabstractIn this paper, we present the Dynamic Small cell Management (DSM) scheme to improve vehicular communications, focusing on the dynamic allocation of small cells when the macrocells cannot cope with the traffic generated by the connected cars. We have considered real base station deployments in the city of Dublin, Ireland, combined with realistic models of vehicle mobility, and small cell deployments. Simulation results demonstrate that our DSM scheme improves communication capabilities (the number of messages correctly received by the infrastructure increases up to a 43.75%), while it also reduces BS overloading (the number of messages managed by the base stations is reduced up to an 8.72%). Therefore, the use of this smart and dynamic solution not only benefits vehicles' communications but also mobile operators. Julio A. Sanguesa, Johann Marquez-Barja, Piedad Garrido, Francisco J. Martinez |
ICCCN | 4 |
| 2017 | When Vehicular Networks meet Artificial IntelligenceabstractIn Vehicular Networks, some applications require a fast and reliable warning data transmission to the Emergency Services and Traffic Authorities. Nevertheless, communication is not always possible in vehicular environments due to the lack of connectivity. To overcome these issues (i.e., signal propagation problem and delayed warning notification time), an effective, smart, cost-effective, and all-purpose RSU deployment policy should be put into place. In this paper, we propose GARSUD, a system which uses a genetic algorithm that is capable to automatically provide a Roadside Unit deployment suitable for any given road map layout. Simulation results show that our proposal is able to reduce the warning notification time --the time required to inform emergency authorities in traffic danger situations-- and to improve vehicular communication capabilities in different flows of traffic at different times during the day. Manuel Fogué, Julio A. Sanguesa, Francisco J. Martinez, Johann Marquez-Barja |
ICTAI | 3 |
| 2016 | Non-emergency patient transport services planning through genetic algorithms
Manuel Fogué, Julio A. Sanguesa, Fernando Naranjo, Jesús Gallardo 0001, Piedad Garrido, Francisco J. Martinez |
Expert Syst. Appl. | 6 |
| 2015 | Extended mobility management and routing protocols for internet-to-VANET multicastingabstractEmerging ITS applications such as fleet management and point of interest distribution require vehicles to have Internet access. However, allowing vehicles to access to the Internet is particularly challenging due to the special characteristics of the vehicular environment. So far, multicasting approaches have been demonstrated to be effective for supporting group communication in traditional networks. However, such Internet-to-VANET multicast service involves several challenges including efficient multicast mobility management and multicast message delivery. This paper proposes a scheme that combines the existing multicast mobility management scheme with vehicular networking solutions to achieve Internet-to-VANET multicasting. The proposed scheme aims to: (i) provide multicast mobility management with low control overhead and efficient bandwidth utilization, as well as (ii) extend the service coverage provided by VANET membership management and multicast message delivery protocol. Simulation results indicate that our Motion-MAODV scheme improves the performance of both MAODV and traditional flooding dissemination schemes in terms of both packet delivery ratio and end-to-end transmission latency. Inès Ben Jemaa, Oyunchimeg Shagdar, Francisco J. Martinez, Piedad Garrido, Fawzi Nashashibi |
CCNC | 3 |
| 2015 | Vehicle Density and Roadmap Topology Issues when Characterizing Vehicular CommunicationsabstractIn this paper, we study the influence of the roadmap topology and the number of vehicles when accounting for the vehicular communications capabilities, especially in urban scenarios. Additionally, we propose the use of two metrics: the SJ Ratio (SJR) and the Total Distance (TD), as the metrics that better correlate with communications performance. Hence, researchers will better characterize the different urban scenarios. In particular, simulation results demonstrate that roadmaps with both similar SJR and TD present similar communications performance in terms of vehicles informed. Julio A. Sanguesa, Fernando Naranjo, Manuel Fogué, Piedad Garrido, Jesús Gallardo 0001, Francisco J. Martinez |
NCA | 7 |
| 2015 | RTAD: A real-time adaptive dissemination system for VANETs
Julio A. Sanguesa, Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
Comput. Commun. | 4 |
| 2014 | Topology-based broadcast schemes for urban scenarios targeting adverse density conditionsabstractResearch works regarding vehicular communications usually obviate assessing the proposals in scenarios including adverse vehicle densities, despite such scenarios are quite common in real urban environments. In this paper, we study the effect of these hostile conditions on the performance of different schemes providing warning message dissemination. We then propose the Junction Store and Forward (JSF) and the Nearest Junction Located (NJL) schemes, which were specially designed to be used in very low and very high density scenarios, respectively. Simulation results using real maps demonstrate how our proposed schemes are able to outperform existing warning message dissemination schemes in urban environments under adverse vehicle density conditions. Julio A. Sanguesa, Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate |
WCNC | 4 |
| 2014 | Reducing emergency services arrival time by using vehicular communications and Evolution Strategies
Javier Barrachina, Piedad Garrido, Manuel Fogué, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
Expert Syst. Appl. | 4 |
| 2014 | A System for Automatic Notification and Severity Estimation of Automotive AccidentsabstractNew communication technologies integrated into modern vehicles offer an opportunity for better assistance to people injured in traffic accidents. Recent studies show how communication capabilities should be supported by artificial intelligence systems capable of automating many of the decisions to be taken by emergency services, thereby adapting the rescue resources to the severity of the accident and reducing assistance time. To improve the overall rescue process, a fast and accurate estimation of the severity of the accident represent a key point to help emergency services better estimate the required resources. This paper proposes a novel intelligent system which is able to automatically detect road accidents, notify them through vehicular networks, and estimate their severity based on the concept of data mining and knowledge inference. Our system considers the most relevant variables that can characterize the severity of the accidents (variables such as the vehicle speed, the type of vehicles involved, the impact speed, and the status of the airbag). Results show that a complete Knowledge Discovery in Databases (KDD) process, with an adequate selection of relevant features, allows generating estimation models that can predict the severity of new accidents. We develop a prototype of our system based on off-the-shelf devices and validate it at the Applus+ IDIADA Automotive Research Corporation facilities, showing that our system can notably reduce the time needed to alert and deploy emergency services after an accident takes place. Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
IEEE Trans. Mob. Comput. | 3 |
| 2013 | Using Evolution Strategies to Reduce Emergency Services Arrival Time in Case of AccidentabstractA critical issue, especially in urban areas, is the occurrence of traffic accidents, since it could generate traffic jams. Additionally, these traffic jams will negatively affect to the rescue process, increasing the emergency services arrival time, which can determine the difference between life or death for injured people involved in the accident. In this paper, we propose four different approaches addressing the traffic congestion problem, comparing them to obtain the best solution. Using V2I communications, we are able to accurately estimate the traffic density in a certain area, which represents a key parameter to perform efficient traffic redirection, thereby reducing the emergency services arrival time, and avoiding traffic jams when an accident occurs. Specifically, we propose two approaches based on the Dijkstra algorithm, and two approaches based on Evolution Strategies. Results indicate that the Density-Based Evolution Strategy system is the best one among all the proposed solutions, since it offers the lowest emergency services travel times. Javier Barrachina, Piedad Garrido, Manuel Fogué, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
ICTAI | 4 |
| 2013 | The Problem of Organizing and Partitioning Large Data Sets in Learning Algorithms for SOM-RBF Mixed Structures - Application to the Approximation of Environmental Variables
José Antonio Torres 0001, Sergio Martínez Tornell, Francisco J. Martinez, Mercedes Peralta |
IJCCI | 3 |
| 2013 | On the use of a Cooperative Neighbor Position Verification scheme to secure warning message dissemination in VANETsabstractEfficient schemes for warning message dissemination in vehicular ad hoc networks (VANETs) use context information collected by vehicles about their neighbor nodes to guide the dissemination process. These schemes maximize their performance when all the vehicles advertise correct information about their positions, and hence position errors may drastically reduce the performance of the dissemination process. We present a proactive Cooperative Neighbor Position and Verification (CNPV) protocol that detects nodes advertising false locations so as to mitigate the impact of adversarial users. We combine our mechanism with two warning dissemination schemes for VANETs, and demonstrate how these algorithms can benefit from the use of our security scheme in the presence of malicious nodes trying to exploit the inherent vulnerabilities of each algorithm. Manuel Fogué, Francisco J. Martinez, Piedad Garrido, Marco Fiore 0001, Carla Fabiana Chiasserini, Claudio Casetti, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
LCN | 2 |
| 2013 | On the selection of optimal broadcast schemes in VANETsabstractIn Vehicular ad hoc Networks (VANETs), efficient dissemination of messages is a key factor to speed up the development of useful services and applications. In this paper, we propose a novel algorithm that automatically chooses the best dissemination scheme trying to fit the warning message delivery policy to the current characteristics of each specific vehicular scenario. Our mechanism uses as input parameters the vehicular density and the topological characteristics of the environment where the vehicles are located, in order to decide which dissemination scheme to use. Simulation results demonstrate the feasibility of our approach, which is able to support more efficient warning message dissemination in vehicular environments. Julio A. Sanguesa, Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
MSWiM | 4 |
| 2013 | Evaluating the Feasibility of Using Smartphones for ITS Safety ApplicationsabstractDriving security and comfort can be improved by applying Intelligent Transportation Systems (ITS) proposals. The low adoption rate of new ITS hardware and software products is slowing down the market introduction of these solutions. In this paper we present a driving safety application for smartphones based on a warning dissemination protocol called eMDR. The use of smartphones minimizes the hardware cost and eliminates most of the adoption barriers; users will no longer have to install new dedicated devices in their vehicles. Instead, they will simply have to install an application in their smartphone. Our application is integrated with a Navigation System which provides access to road maps, current location, and route information. We analyzed the behavior of the wireless channel and the GPS location service under different conditions to assess the feasibility of our proposal. Results showed that, in C2C communications, smartphones are able to provide a reasonable degree of connectivity, and that the degree of precision achieved is enough for certain types of driving safety applications. Sergio Martínez Tornell, Carlos T. Calafate, Juan-Carlos Cano, Pietro Manzoni, Manuel Fogué, Francisco J. Martinez |
VTC Spring | 6 |
| 2013 | Assessing vehicular density estimation using vehicle-to-infrastructure communicationsabstractVehicle density is one of the main metrics used for assessing the road traffic conditions. In this paper, we present a solution to estimate the density of vehicles that has been specially designed for Vehicular Networks. Our proposal allows Intelligent Transportation Systems to continuously estimate the vehicular density by accounting for the number of beacons received per Road Side Unit, as well as the roadmap topology. Simulation results indicate that our approach accurately estimates the vehicular density, and therefore automatic traffic controlling systems may use it to predict traffic jams and introduce countermeasures. Javier Barrachina, Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
WOWMOM | 4 |
| 2013 | A novel approach for traffic accidents sanitary resource allocation based on multi-objective genetic algorithms
Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
Expert Syst. Appl. | 3 |
| 2013 | An Adaptive System Based on Roadmap Profiling to Enhance Warning Message Dissemination in VANETsabstractIn recent years, new applications, architectures, and technologies have been proposed for vehicular ad hoc networks (VANETs). Regarding traffic safety applications for VANETs, warning messages have to be quickly and smartly disseminated in order to reduce the required dissemination time and to increase the number of vehicles receiving the traffic warning information. In the past, several approaches have been proposed to improve the alert dissemination process in multihop wireless networks, but none of them were tested in real urban scenarios, adapting its behavior to the propagation features of the scenario. In this paper, we present the Profile-driven Adaptive Warning Dissemination Scheme (PAWDS) designed to improve the warning message dissemination process. With respect to previous proposals, our proposed scheme uses a mapping technique based on adapting the dissemination strategy according to both the characteristics of the street area where the vehicles are moving and the density of vehicles in the target scenario. Our algorithm reported a noticeable improvement in the performance of alert dissemination processes in scenarios based on real city maps. Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
IEEE/ACM Trans. Netw. | 3 |
| 2012 | Free software at the education service in accordance with the lawabstractNowadays, protection of personal data is an important issue when developing software. In 1999, the Organic Law of Personal Data (LOPD) was passed in Spain. According to this Law, every computer application which works with personal data has to be adapted to be in accordance with the LOPD requirements. However, there is no doubt that many personal data is currently improperly managed, especially by education centers and professors. This article presents GADM (Gestor de Alumnos para Dispositivos Móviles), an ad-hoc free software specially designed to help teachers to manage and monitor school information about the students' progress, their evaluation marks, etc. Moreover, GADM offers secure communications and appropriate management of such kind of data in educational environments. Our application has been tested by several teachers at the secondary education stage, with very satisfactory results. Javier Barrachina, Piedad Garrido, Francisco J. Martinez, Fernando Repulles |
EDUCON | 3 |
| 2012 | CAOVA: A Car Accident Ontology for VANETsabstractIn a near future, vehicles will be provided with a variety of new sensors capable of gathering information from their surroundings. These vehicles will also be capable of sharing the harvested information via Vehicular Ad hoc NETworks (VANETs) with nearby vehicles, or with the emergency services in case of an accident. Hence, distributed applications based on VANETs will need to agree on a `common understanding' of context for interoperability, and therefore, it is necessary to create a standard structure which enables data interoperability among all the different entities involved in transportation systems. In this paper, we focus on traffic safety; specifically, we present a Car Accident lightweight Ontology for VANETs (CAOVA). The instances of our ontology are filled with: (i) the information collected when an accident occurs, and (ii) the data available in the General Estimates System (GES) accidents database. We assess the reliability of our proposal in two different ways: one via realistic crash tests, and the other one using a network simulation framework. Javier Barrachina, Piedad Garrido, Manuel Fogué, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
WCNC | 4 |
| 2012 | VEACON: A Vehicular Accident Ontology designed to improve safety on the roads
Javier Barrachina, Piedad Garrido, Manuel Fogué, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
J. Netw. Comput. Appl. | 4 |
| 2011 | Using roadmap profiling to enhance the warning message dissemination in vehicular environmentsabstractIn recent years, new applications, architectures and technologies have been proposed for Vehicular ad hoc networks (VANETs). Regarding traffic safety applications for VANETs, warning messages have to be quickly disseminated in order to reduce the required dissemination time and to increase the number of vehicles receiving the traffic warning information. In the past, several approaches have been proposed to improve the alert dissemination process in multi-hop wireless networks, but none of them is adapted to the propagation features of the scenario. In this paper, we present an adaptive algorithm designed to improve the warning message dissemination process. With respect to previous proposals, our proposed scheme uses a mapping technique based on adapting the dissemination strategy according to the characteristics of the street area where the vehicles are moving. Our algorithm reported a noticeable improvement in the performance of alert dissemination processes in simulated scenarios based on real city maps. Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
LCN | 3 |
| 2011 | Analysis of the Most Representative Factors Affecting Warning Message Dissemination in VANETs under Real RoadmapsabstractIn recent years, new architectures and technologies have been proposed for Vehicular ad hoc networks (VANETs).However, the experiments to validate these proposals tend to overlook the most important and representative factors. Moreover, the scenarios simulated tend to be very simplistic (highways or Manhattan-based layouts), which could seriously affect the validity of the obtained results. In this paper, we present a statistical analysis based on the 2kfactorial methodology to determine the most representative factors affecting traffic safety applications under real roadmaps. Our purpose is to determine which are the key factors affecting Warning Message Dissemination (WMD) in order to concentrate on such parameters, thus reducing the amount of simulation time required. Simulation results show that the key factors affecting warning messages delivery are the density of vehicles, and the roadmap used. Based on this statistical analysis, we consider that VANET researchers must evaluate the benefits of their proposals using different vehicle densities and city scenarios. Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
MASCOTS | 3 |
| 2011 | PAWDS: A Roadmap Profile-Driven Adaptive System for Alert Dissemination in VANETsabstractIn traffic safety applications for Vehicular Ad hoc Networks (VANETs), warning messages have to be disseminated whenever a dangerous situation occurs to alert nearby vehicles. Using inefficient broadcast schemes may lead to ineffective dissemination of warning messages causing broadcast storm problems. In the past, several approaches have been proposed to reduce the so called broadcast storm in multi-hop wireless networks, but none of them is adapted to the features of the propagation scenario. In this paper, we present the Profile-driven Adaptive Warning Dissemination Scheme (PAWDS) to improve the warning message dissemination process. With respect to previous proposals, our PAWDS scheme uses an adaptive technique based on tuning the operation of the dissemination scheme according to the characteristics of the street area where the vehicles are moving. Our algorithm reported a noticeable improvement in the performance of alert dissemination processes in simulated scenarios based on real city maps. Manuel Fogué, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
NCA | 3 |
| 2011 | A survey and comparative study of simulators for vehicular ad hoc networks (VANETs)abstractAbstract Wireless communication technologies have now greatly impact our daily lives. From indoor wireless LANs to outdoor cellular mobile networks, wireless technologies have benefited billions of users around the globe. The era of vehicular ad hoc networks (VANETs) is now evolving, gaining attention and momentum. Researchers and developers have built VANET simulation software to allow the study and evaluation of various media access, routing, and emergency warning protocols. VANET simulation is fundamentally different from MANETs (mobile ad hoc networks) simulation because in VANETs, vehicular environment imposes new issues and requirements, such as constrained road topology, multi‐path fading and roadside obstacles, traffic flow models, trip models, varying vehicular speed and mobility, traffic lights, traffic congestion, drivers' behavior, etc. Currently, there are VANET mobility generators, network simulators, and VANET simulators. This paper presents a comprehensive study and comparisons of the various publicly available VANET simulation software and their components. In particular, we contrast their software characteristics, graphical user interface (GUI), popularity, ease of use, input requirements, output visualization capability, accuracy of simulation, etc. Finally, while each of the studied simulators provides a good simulation environment for VANETs, refinements and further contributions are needed before they can be widely used by the research community. Copyright © 2009 John Wiley & Sons, Ltd. Francisco J. Martinez, Chai-Keong Toh, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
Wirel. Commun. Mob. Comput. | 1 |
| 2010 | Enhancing Intelligent Pedagogical Agents in Virtual Worlds
Piedad Garrido, Francisco J. Martinez, Christian Gütl, Inmaculada Plaza |
ICCE | 2 |
| 2010 | Assessing the Impact of a Realistic Radio Propagation Model on VANET Scenarios Using Real MapsabstractResearch in Vehicular Ad hoc Networks (VANETs) has found in simulation the most useful method to test new algorithms and techniques. This is mainly due to the high cost of deploying such systems in real scenarios. However, when determining the factors that should be taken into account in these simulations, some features such as using real topologies, radio signal absorption due to obstacles and channel access are rarely included, and therefore, results obtained are far from being realistic. In this paper, we present a new Radio Propagation Model (RPM), called Real Attenuation and Visibility (RAV), proposed to simulate more realistically both attenuation of wireless signals (signal power loss) and the radio visibility scheme (presence of obstacles interfering with the signal path). We evaluated this model and compared it against existing RPMs using real scenarios. Simulation results confirmed that our proposed RAV scheme can better reflect realistic scenarios. Francisco J. Martinez, Manuel Fogué, Manuel Coll, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
NCA | 1 |
| 2010 | Evaluating the Impact of a Novel Warning Message Dissemination Scheme for VANETs Using Real City Maps
Francisco J. Martinez, Manuel Fogué, Manuel Coll, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
Networking | 1 |
| 2009 | A performance evaluation of warning message dissemination in 802.11p based VANETsabstractIn this paper, we present a performance evaluation study analyzing the behavior of a generic warning message dissemination (WMD) mechanism in a 802.11p based VANET. In our WMD method, warning-mode vehicles notify nearby vehicles in order to improve traffic safety and to control traffic congestion. Our evaluation uses 2k factorial methodology to determine the most representative factors that affect WMD performance. We performed simulations to evaluate the impact of different characterizing factors. Performance metrics evaluated are: (a) the time required to propagate the warning messages, (b) the number of blind nodes (i.e., nodes that do not receive these packets), and (c) the number of packets received per node. Simulation results show that the propagation delay is lower when node density increases, and that the percentage of blind nodes highly depends on this factor too. Factors that affect the number of packets received include downtown size, the probability of being in downtown, and the number of nodes. Lastly, we discovered that the size of packets sent does not significantly impact WMD performance. Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
LCN | 1 |
| 2009 | Realistic radio propagation models (RPMs) for VANET simulationsabstractDeploying and testing vehicular ad hoc networks (VANETs) involves high cost and intensive labor. Hence simulation is a useful alternative prior to actual implementation. Most works found in the literature employ very simplistic radio propagation models (RPMs), ignoring the dramatic effects presented by buildings on radio signals. In this paper, we present three different RPMs that increase the level of realism, thereby allowing us to obtain more accurate and meaningful results. These models are: (a) the distance attenuation model (DAM), (b) the building model (BM), and (c) the building and distance attenuation model (BDAM). We evaluated these different models and compared them with the two-ray ground model implemented in ns-2. We then carried out further study to evaluate the impact of varying some important parameters such as vehicle density and building size on VANET warning message dissemination. Simulation results confirmed that our proposed BDAM significantly affects the percentage of blind vehicles present and the number of received warning messages, and that our models can better reflect realistic scenarios. Francisco J. Martinez, Chai-Keong Toh, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni |
WCNC | 1 |