Probe-based end-to-end overload control for networks of SIP servers

The Session Initiation Protocol (SIP) has been adopted by the IETF as the control protocol for creating, modifying and terminating multimedia sessions. Overload occurs in SIP networks when SIP servers have insufficient resources to handle received messages. Under overload, SIP networks may suffer from congestion collapse due to current ineffective SIP overload control mechanisms. This paper introduces a probe-based end-to-end overload control (PEOC) mechanism, which is deployed at the edge servers of SIP networks and is easy to implement. By probing the SIP network with SIP messages, PEOC estimates the network load and controls the traffic admitted to the network according to the estimated load. Theoretic analysis and extensive simulations verify that PEOC can keep high throughput for SIP networks even when the offered load exceeds the capacity of the network. Besides, it can respond quickly to the sudden variations of the offered load and achieve good fairness.

Correlation Dimension of Complex Networks

We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.

Empirical analysis of traffic volume for the application of the options theory to highway concessions

*************************************************************************************** EL WCTR es un Congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte que hasta el 2010 publicaba sus libros de abstracts con ISBN. Por ello consideramos que debería seguir teníendose en cuenta para los indicadores de calidad ******************************************************************************************* Investment projects in the field of transportation infrastructures have a high degree of uncertainty and require an important amount of resources. In highway concessions in particular, the calculation of the Net Present Value (NPV) of the project by means of the discount of cash flows, may lead to erroneous results when the project incorporates certain flexibility. In these cases, the theory of real options is an alternative tool for the valuation of concessions. When the variable that generates uncertainty (in our case, the traffic) follows a random walk (or Geometric Brownian Motion), we can calculate the value of the options embedded in the contract starting directly from the process followed by that variable. This procedure notably simplifies the calculation method. In order to test the hypothesis of the evolution of traffic as a Geometric Brownian Motion, we have used the available series of traffic in Spanish highways, and we have applied the Augmented Dickey-Fuller approach, which is the most widely used test for this kind of study. The main result of the analysis is that we cannot reject the hypothesis that traffic follows a Geometric Brownian Motion in the majority of both toll highways and free highways in Spain.

Agent-based modeling and simulation for the design of the future european Air Traffic Management system: the experience of CASSIOPEIA

The SESAR (Single European Sky ATM Research) program is an ambitious re-search and development initiative to design the future European air traffic man-agement (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three stud-ies related to the design of future ATM systems in Europe.

Knowledge-based models for adaptive traffic management systems

This paper describes a general approach for real time traffic management support using knowledge based models. Recognizing that human intervention is usually required to apply the current automatic traffic control systems, it is argued that there is a need for an additional intelligent layer to help operators to understand traffic problems and to make the best choice of strategic control actions that modify the assumption framework of the existing systems.

Bus line classification using neural networks

Grouping urban bus routes is necessary when there are evidences of significant differences among them. In Jiménez et al. (2013), a reduced sample of routes was grouped into clusters utilizing kinematic measured data. As a further step, in this paper, the remaining urban bus routes of a city, for which no kinematic measurements are available, are classified. For such purpose we use macroscopic geographical and functional variables to describe each route, while the clustering process is performed by means of a neural network. Limitations caused by reduced training samples are solved using the bootstrap method.

Recovery of Disruptions in Rapid Transit Networks

This paper studies the disruption management problem of rapid transit rail networks. Besides optimizing the timetable and the rolling stock schedules, we explicitly deal with the effects of the disruption on the passenger demand. We propose a two-step approach that combines an integrated optimization model (for the timetable and rolling stock) with a model for the passengers’ behavior. We report our computational tests on realistic problem instances of the Spanish rail operator RENFE. The proposed approach is able to find solutions with a very good balance between various managerial goals within a few minutes. Se estudia la gestión de las incidencias en redes de metro y cercanías. Se optimizan los horarios y la asignación del material rodante, teniendo en cuenta el comportamiento de los pasajeros. Se reallizan pruebas en varias líneas de la red de cercanías de Madrid, con resultados satisfactorios.

Reduced carbon and energy footprint in highway operations: the Highway Energy Assessment (HERA) methodology

Global demand for mobility is increasing and the environmental impact of transport has become an important issue in transportation network planning and decision-making, as well as in the operational management phase. Suitable methods are required to assess emissions and fuel consumption reduction strategies that seek to improve energy efficiency and furthering decarbonization. This study describes the development and application of an improved modeling framework – the HERA (Highway EneRgy Assessment) methodology – that enables to assess the energy and carbon footprint of different highways and traffic flow scenarios and their comparison. HERA incorporates an average speed consumption model adjusted with a correction factor which takes into account the road gradient. It provides a more comprehensive method for estimating the footprint of particular highway segments under specific traffic conditions. It includes the application of the methodology to the Spanish highway network to validate it. Finally, a case study shows the benefits from using this methodology and how to integrate the objective of carbon footprint reductions into highway design, operation and scenario comparison.

Event-based time series data preprocessing: application to traffic flow time series

Traffic flow time series data are usually high dimensional and very complex. Also they are sometimes imprecise and distorted due to data collection sensor malfunction. Additionally, events like congestion caused by traffic accidents add more uncertainty to real-time traffic conditions, making traffic flow forecasting a complicated task. This article presents a new data preprocessing method targeting multidimensional time series with a very high number of dimensions and shows its application to real traffic flow time series from the California Department of Transportation (PEMS web site). The proposed method consists of three main steps. First, based on a language for defining events in multidimensional time series, mTESL, we identify a number of types of events in time series that corresponding to either incorrect data or data with interference. Second, each event type is restored utilizing an original method that combines real observations, local forecasted values and historical data. Third, an exponential smoothing procedure is applied globally to eliminate noise interference and other random errors so as to provide good quality source data for future work.

Propuesta de un marco conceptual para el análisis comparativo de las redes de distribución de dos supermercados online = Proposal of a conceptual framework for the comparative analysis of the distribution networks of two online supermarkets

In this article the network configuration for fulfillment and distribution of online orders of two British retailers is analyzed and compared. For this purpose, it is proposed a conceptual framework that consists of the key following aspects: network configuration, transportation management and location of demand. As a result is not obvious to determine the ideal centralization degree in each case. Finally, it is suggested the future development of an analytic tool that helps to choose the most appropriate model.

Evaluation of configurations of supply networks supported by it systems

Los sistemas transaccionales tales como los programas informáticos para la planificación de recursos empresariales (ERP software) se han implementado ampliamente mientras que los sistemas analíticos para la gestión de la cadena de suministro (SCM software) no han tenido el éxito deseado por la industria de tecnología de información (TI). Aunque se documentan beneficios importantes derivados de las implantaciones de SCM software, las empresas industriales son reacias a invertir en este tipo de sistemas. Por una parte esto es debido a la falta de métodos que son capaces de detectar los beneficios por emplear esos sistemas, y por otra parte porque el coste asociado no está identificado, detallado y cuantificado suficientemente. Los esquemas de coordinación basados únicamente en sistemas ERP son alternativas válidas en la práctica industrial siempre que la relación coste-beneficio esta favorable. Por lo tanto, la evaluación de formas organizativas teniendo en cuenta explícitamente el coste debido a procesos administrativos, en particular por ciclos iterativos, es de gran interés para la toma de decisiones en el ámbito de inversiones en TI. Con el fin de cerrar la brecha, el propósito de esta investigación es proporcionar métodos de evaluación que permitan la comparación de diferentes formas de organización y niveles de soporte por sistemas informáticos. La tesis proporciona una amplia introducción, analizando los retos a los que se enfrenta la industria. Concluye con las necesidades de la industria de SCM software: unas herramientas que facilitan la evaluación integral de diferentes propuestas de organización. A continuación, la terminología clave se detalla centrándose en la teoría de la organización, las peculiaridades de inversión en TI y la tipología de software de gestión de la cadena de suministro. La revisión de la literatura clasifica las contribuciones recientes sobre la gestión de la cadena de suministro, tratando ambos conceptos, el diseño de la organización y su soporte por las TI. La clasificación incluye criterios relacionados con la metodología de la investigación y su contenido. Los estudios empíricos en el ámbito de la administración de empresas se centran en tipologías de redes industriales. Nuevos algoritmos de planificación y esquemas de coordinación innovadoras se desarrollan principalmente en el campo de la investigación de operaciones con el fin de proponer nuevas funciones de software. Artículos procedentes del área de la gestión de la producción se centran en el análisis de coste y beneficio de las implantaciones de sistemas. La revisión de la literatura revela que el éxito de las TI para la coordinación de redes industriales depende en gran medida de características de tres dimensiones: la configuración de la red industrial, los esquemas de coordinación y las funcionalidades del software. La literatura disponible está enfocada sobre todo en los beneficios de las implantaciones de SCM software. Sin embargo, la coordinación de la cadena de suministro, basándose en el sistema ERP, sigue siendo la práctica industrial generalizada, pero el coste de coordinación asociado no ha sido abordado por los investigadores. Los fundamentos de diseño organizativo eficiente se explican en detalle en la medida necesaria para la comprensión de la síntesis de las diferentes formas de organización. Se han generado varios esquemas de coordinación variando los siguientes parámetros de diseño: la estructura organizativa, los mecanismos de coordinación y el soporte por TI. Las diferentes propuestas de organización desarrolladas son evaluadas por un método heurístico y otro basado en la simulación por eventos discretos. Para ambos métodos, se tienen en cuenta los principios de la teoría de la organización. La falta de rendimiento empresarial se debe a las dependencias entre actividades que no se gestionan adecuadamente. Dentro del método heurístico, se clasifican las dependencias y se mide su intensidad basándose en factores contextuales. A continuación, se valora la idoneidad de cada elemento de diseño organizativo para cada dependencia específica. Por último, cada forma de organización se evalúa basándose en la contribución de los elementos de diseño tanto al beneficio como al coste. El beneficio de coordinación se refiere a la mejora en el rendimiento logístico - este concepto es el objeto central en la mayoría de modelos de evaluación de la gestión de la cadena de suministro. Por el contrario, el coste de coordinación que se debe incurrir para lograr beneficios no se suele considerar en detalle. Procesos iterativos son costosos si se ejecutan manualmente. Este es el caso cuando SCM software no está implementada y el sistema ERP es el único instrumento de coordinación disponible. El modelo heurístico proporciona un procedimiento simplificado para la clasificación sistemática de las dependencias, la cuantificación de los factores de influencia y la identificación de configuraciones que indican el uso de formas organizativas y de soporte de TI más o menos complejas. La simulación de eventos discretos se aplica en el segundo modelo de evaluación utilizando el paquete de software ‘Plant Simulation’. Con respecto al rendimiento logístico, por un lado se mide el coste de fabricación, de inventario y de transporte y las penalizaciones por pérdida de ventas. Por otro lado, se cuantifica explícitamente el coste de la coordinación teniendo en cuenta los ciclos de coordinación iterativos. El método se aplica a una configuración de cadena de suministro ejemplar considerando diversos parámetros. Los resultados de la simulación confirman que, en la mayoría de los casos, el beneficio aumenta cuando se intensifica la coordinación. Sin embargo, en ciertas situaciones en las que se aplican ciclos de planificación manuales e iterativos el coste de coordinación adicional no siempre conduce a mejor rendimiento logístico. Estos resultados inesperados no se pueden atribuir a ningún parámetro particular. La investigación confirma la gran importancia de nuevas dimensiones hasta ahora ignoradas en la evaluación de propuestas organizativas y herramientas de TI. A través del método heurístico se puede comparar de forma rápida, pero sólo aproximada, la eficiencia de diferentes formas de organización. Por el contrario, el método de simulación es más complejo pero da resultados más detallados, teniendo en cuenta parámetros específicos del contexto del caso concreto y del diseño organizativo. ABSTRACT Transactional systems such as Enterprise Resource Planning (ERP) systems have been implemented widely while analytical software like Supply Chain Management (SCM) add-ons are adopted less by manufacturing companies. Although significant benefits are reported stemming from SCM software implementations, companies are reluctant to invest in such systems. On the one hand this is due to the lack of methods that are able to detect benefits from the use of SCM software and on the other hand associated costs are not identified, detailed and quantified sufficiently. Coordination schemes based only on ERP systems are valid alternatives in industrial practice because significant investment in IT can be avoided. Therefore, the evaluation of these coordination procedures, in particular the cost due to iterations, is of high managerial interest and corresponding methods are comprehensive tools for strategic IT decision making. The purpose of this research is to provide evaluation methods that allow the comparison of different organizational forms and software support levels. The research begins with a comprehensive introduction dealing with the business environment that industrial networks are facing and concludes highlighting the challenges for the supply chain software industry. Afterwards, the central terminology is addressed, focusing on organization theory, IT investment peculiarities and supply chain management software typology. The literature review classifies recent supply chain management research referring to organizational design and its software support. The classification encompasses criteria related to research methodology and content. Empirical studies from management science focus on network types and organizational fit. Novel planning algorithms and innovative coordination schemes are developed mostly in the field of operations research in order to propose new software features. Operations and production management researchers realize cost-benefit analysis of IT software implementations. The literature review reveals that the success of software solutions for network coordination depends strongly on the fit of three dimensions: network configuration, coordination scheme and software functionality. Reviewed literature is mostly centered on the benefits of SCM software implementations. However, ERP system based supply chain coordination is still widespread industrial practice but the associated coordination cost has not been addressed by researchers. Fundamentals of efficient organizational design are explained in detail as far as required for the understanding of the synthesis of different organizational forms. Several coordination schemes have been shaped through the variation of the following design parameters: organizational structuring, coordination mechanisms and software support. The different organizational proposals are evaluated using a heuristic approach and a simulation-based method. For both cases, the principles of organization theory are respected. A lack of performance is due to dependencies between activities which are not managed properly. Therefore, within the heuristic method, dependencies are classified and their intensity is measured based on contextual factors. Afterwards the suitability of each organizational design element for the management of a specific dependency is determined. Finally, each organizational form is evaluated based on the contribution of the sum of design elements to coordination benefit and to coordination cost. Coordination benefit refers to improvement in logistic performance – this is the core concept of most supply chain evaluation models. Unfortunately, coordination cost which must be incurred to achieve benefits is usually not considered in detail. Iterative processes are costly when manually executed. This is the case when SCM software is not implemented and the ERP system is the only available coordination instrument. The heuristic model provides a simplified procedure for the classification of dependencies, quantification of influence factors and systematic search for adequate organizational forms and IT support. Discrete event simulation is applied in the second evaluation model using the software package ‘Plant Simulation’. On the one hand logistic performance is measured by manufacturing, inventory and transportation cost and penalties for lost sales. On the other hand coordination cost is explicitly considered taking into account iterative coordination cycles. The method is applied to an exemplary supply chain configuration considering various parameter settings. The simulation results confirm that, in most cases, benefit increases when coordination is intensified. However, in some situations when manual, iterative planning cycles are applied, additional coordination cost does not always lead to improved logistic performance. These unexpected results cannot be attributed to any particular parameter. The research confirms the great importance of up to now disregarded dimensions when evaluating SCM concepts and IT tools. The heuristic method provides a quick, but only approximate comparison of coordination efficiency for different organizational forms. In contrast, the more complex simulation method delivers detailed results taking into consideration specific parameter settings of network context and organizational design.

How should the sustainability of the location of dry ports be measured? A proposed methodology using Bayesian networks and multi-criteria decision analysis

The global economic structure, with its decentralized production and the consequent increase in freight traffic all over the world, creates considerable problems and challenges for the freight transport sector. This situation has led shipping to become the most suitable and cheapest way to transport goods. Thus, ports are configured as nodes with critical importance in the logistics supply chain as a link between two transport systems, sea and land. Increase in activity at seaports is producing three undesirable effects: increasing road congestion, lack of open space in port installations and a significant environmental impact on seaports. These adverse effects can be mitigated by moving part of the activity inland. Implementation of dry ports is a possible solution and would also provide an opportunity to strengthen intermodal solutions as part of an integrated and more sustainable transport chain, acting as a link between road and railway networks. In this sense, implementation of dry ports allows the separation of the links of the transport chain, thus facilitating the shortest possible routes for the lowest capacity and most polluting means of transport. Thus, the decision of where to locate a dry port demands a thorough analysis of the whole logistics supply chain, with the objective of transferring the largest volume of goods possible from road to more energy efficient means of transport, like rail or short-sea shipping, that are less harmful to the environment. However, the decision of where to locate a dry port must also ensure the sustainability of the site. Thus, the main goal of this article is to research the variables influencing the sustainability of dry port location and how this sustainability can be evaluated. With this objective, in this paper we present a methodology for assessing the sustainability of locations by the use of Multi-Criteria Decision Analysis (MCDA) and Bayesian Networks (BNs). MCDA is used as a way to establish a scoring, whilst BNs were chosen to eliminate arbitrariness in setting the weightings using a technique that allows us to prioritize each variable according to the relationships established in the set of variables. In order to determine the relationships between all the variables involved in the decision, giving us the importance of each factor and variable, we built a K2 BN algorithm. To obtain the scores of each variable, we used a complete cartography analysed by ArcGIS. Recognising that setting the most appropriate location to place a dry port is a geographical multidisciplinary problem, with significant economic, social and environmental implications, we consider 41 variables (grouped into 17 factors) which respond to this need. As a case of study, the sustainability of all of the 10 existing dry ports in Spain has been evaluated. In this set of logistics platforms, we found that the most important variables for achieving sustainability are those related to environmental protection, so the sustainability of the locations requires a great respect for the natural environment and the urban environment in which they are framed.

Self-adaptive strategy based on fuzzy control systems for improving performance in wireless sensors networks

The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

Predicción de tráfico de contenedores a corto plazo mediante técnicas de minería de datos : redes neuronales artificiales y redes bayesianas

El correcto pronóstico en el ámbito de la logística de transportes es de vital importancia para una adecuada planificación de medios y recursos, así como de su optimización. Hasta la fecha los estudios sobre planificación portuaria se basan principalmente en modelos empíricos; que se han utilizado para planificar nuevas terminales y desarrollar planes directores cuando no se dispone de datos iniciales, analíticos; más relacionados con la teoría de colas y tiempos de espera con formulaciones matemáticas complejas y necesitando simplificaciones de las mismas para hacer manejable y práctico el modelo o de simulación; que requieren de una inversión significativa como para poder obtener resultados aceptables invirtiendo en programas y desarrollos complejos. La Minería de Datos (MD) es un área moderna interdisciplinaria que engloba a aquellas técnicas que operan de forma automática (requieren de la mínima intervención humana) y, además, son eficientes para trabajar con las grandes cantidades de información disponible en las bases de datos de numerosos problemas prácticos. La aplicación práctica de estas disciplinas se extiende a numerosos ámbitos comerciales y de investigación en problemas de predicción, clasificación o diagnosis. Entre las diferentes técnicas disponibles en minería de datos las redes neuronales artificiales (RNA) y las redes probabilísticas o redes bayesianas (RB) permiten modelizar de forma conjunta toda la información relevante para un problema dado. En el presente trabajo se han analizado dos aplicaciones de estos casos al ámbito portuario y en concreto a contenedores. En la Tesis Doctoral se desarrollan las RNA como herramienta para obtener previsiones de tráfico y de recursos a futuro de diferentes puertos, a partir de variables de explotación, obteniéndose valores continuos. Para el caso de las redes bayesianas (RB), se realiza un trabajo similar que para el caso de las RNA, obteniéndose valores discretos (un intervalo). El principal resultado que se obtiene es la posibilidad de utilizar tanto las RNA como las RB para la estimación a futuro de parámetros físicos, así como la relación entre los mismos en una terminal para una correcta asignación de los medios a utilizar y por tanto aumentar la eficiencia productiva de la terminal. Como paso final se realiza un estudio de complementariedad de ambos modelos a corto plazo, donde se puede comprobar la buena aceptación de los resultados obtenidos. Por tanto, se puede concluir que estos métodos de predicción pueden ser de gran ayuda a la planificación portuaria. The correct assets’ forecast in the field of transportation logistics is a matter of vital importance for a suitable planning and optimization of the necessary means and resources. Up to this date, ports planning studies were basically using empirical models to deal with new terminals planning or master plans development when no initial data are available; analytical models, more connected to the queuing theory and the waiting times, and very complicated mathematical formulations requiring significant simplifications to acquire a practical and easy to handle model; or simulation models, that require a significant investment in computer codes and complex developments to produce acceptable results. The Data Mining (DM) is a modern interdisciplinary field that include those techniques that operate automatically (almost no human intervention is required) and are highly efficient when dealing with practical problems characterized by huge data bases containing significant amount of information. These disciplines’ practical application extends to many commercial or research fields, dealing with forecast, classification or diagnosis problems. Among the different techniques of the Data Mining, the Artificial Neuronal Networks (ANN) and the probabilistic – or Bayesian – networks (BN) allow the joint modeling of all the relevant information for a given problem. This PhD work analyses their application to two practical cases in the ports field, concretely to container terminals. This PhD work details how the ANN have been developed as a tool to produce traffic and resources forecasts for several ports, based on exploitation variables to obtain continuous values. For the Bayesian networks case (BN), a similar development has been carried out, obtaining discreet values (an interval). The main finding is the possibility to use ANN and BN to estimate future needs of the port’s or terminal’s physical parameters, as well as the relationship between them within a specific terminal, that allow a correct assignment of the necessary means and, thus, to increase the terminal’s productive efficiency. The final step is a short term complementarily study of both models, carried out in order to verify the obtained results. It can thus be stated that these prediction methods can be a very useful tool in ports’ planning.

Cognitive strategies for security in wireless sensor networks

Las redes de sensores inalámbricas son uno de los sectores con más crecimiento dentro de las redes inalámbricas. La rápida adopción de estas redes como solución para muchas nuevas aplicaciones ha llevado a un creciente tráfico en el espectro radioeléctrico. Debido a que las redes inalámbricas de sensores operan en las bandas libres Industrial, Scientific and Medical (ISM) se ha producido una saturación del espectro que en pocos años no permitirá un buen funcionamiento. Con el objetivo de solucionar este tipo de problemas ha aparecido el paradigma de Radio Cognitiva (CR). La introducción de las capacidades cognitivas en las redes inalámbricas de sensores permite utilizar estas redes para aplicaciones con unos requisitos más estrictos respecto a fiabilidad, cobertura o calidad de servicio. Estas redes que aúnan todas estas características son llamadas redes de sensores inalámbricas cognitivas (CWSNs). La mejora en prestaciones de las CWSNs permite su utilización en aplicaciones críticas donde antes no podían ser utilizadas como monitorización de estructuras, de servicios médicos, en entornos militares o de vigilancia. Sin embargo, estas aplicaciones también requieren de otras características que la radio cognitiva no nos ofrece directamente como, por ejemplo, la seguridad. La seguridad en CWSNs es un aspecto poco desarrollado al ser una característica no esencial para su funcionamiento, como pueden serlo el sensado del espectro o la colaboración. Sin embargo, su estudio y mejora es esencial de cara al crecimiento de las CWSNs. Por tanto, esta tesis tiene como objetivo implementar contramedidas usando las nuevas capacidades cognitivas, especialmente en la capa física, teniendo en cuenta las limitaciones con las que cuentan las WSNs. En el ciclo de trabajo de esta tesis se han desarrollado dos estrategias de seguridad contra ataques de especial importancia en redes cognitivas: el ataque de simulación de usuario primario (PUE) y el ataque contra la privacidad eavesdropping. Para mitigar el ataque PUE se ha desarrollado una contramedida basada en la detección de anomalías. Se han implementado dos algoritmos diferentes para detectar este ataque: el algoritmo de Cumulative Sum y el algoritmo de Data Clustering. Una vez comprobado su validez se han comparado entre sí y se han investigado los efectos que pueden afectar al funcionamiento de los mismos. Para combatir el ataque de eavesdropping se ha desarrollado una contramedida basada en la inyección de ruido artificial de manera que el atacante no distinga las señales con información del ruido sin verse afectada la comunicación que nos interesa. También se ha estudiado el impacto que tiene esta contramedida en los recursos de la red. Como resultado paralelo se ha desarrollado un marco de pruebas para CWSNs que consta de un simulador y de una red de nodos cognitivos reales. Estas herramientas han sido esenciales para la implementación y extracción de resultados de la tesis. ABSTRACT Wireless Sensor Networks (WSNs) are one of the fastest growing sectors in wireless networks. The fast introduction of these networks as a solution in many new applications has increased the traffic in the radio spectrum. Due to the operation of WSNs in the free industrial, scientific, and medical (ISM) bands, saturation has ocurred in these frequencies that will make the same operation methods impossible in the future. Cognitive radio (CR) has appeared as a solution for this problem. The networks that join all the mentioned features together are called cognitive wireless sensor networks (CWSNs). The adoption of cognitive features in WSNs allows the use of these networks in applications with higher reliability, coverage, or quality of service requirements. The improvement of the performance of CWSNs allows their use in critical applications where they could not be used before such as structural monitoring, medical care, military scenarios, or security monitoring systems. Nevertheless, these applications also need other features that cognitive radio does not add directly, such as security. The security in CWSNs has not yet been explored fully because it is not necessary field for the main performance of these networks. Instead, other fields like spectrum sensing or collaboration have been explored deeply. However, the study of security in CWSNs is essential for their growth. Therefore, the main objective of this thesis is to study the impact of some cognitive radio attacks in CWSNs and to implement countermeasures using new cognitive capabilities, especially in the physical layer and considering the limitations of WSNs. Inside the work cycle of this thesis, security strategies against two important kinds of attacks in cognitive networks have been developed. These attacks are the primary user emulator (PUE) attack and the eavesdropping attack. A countermeasure against the PUE attack based on anomaly detection has been developed. Two different algorithms have been implemented: the cumulative sum algorithm and the data clustering algorithm. After the verification of these solutions, they have been compared and the side effects that can disturb their performance have been analyzed. The developed approach against the eavesdropping attack is based on the generation of artificial noise to conceal information messages. The impact of this countermeasure on network resources has also been studied. As a parallel result, a new framework for CWSNs has been developed. This includes a simulator and a real network with cognitive nodes. This framework has been crucial for the implementation and extraction of the results presented in this thesis.