A Classification and Performance Comparison of Mobility Models for Ad Hoc Networks

Abstract. In mobile ad hoc network research, simulation plays an important role in determining the network characteristics and measuring performance. On the other hand, unrealistic simulation conditions may be misleading, instead of being explanatory. For this reason, constructing simulation models closer to the real circumstances is very significant. Movement behavior of mobile entities is one of the most important concepts for the realistic simulation scenarios in mo-bile ad hoc networks. In this study, we first provide a survey and a new hybrid classification of existing mobility models in the literature. We implemented the random direction and boundless simulation area models on Scalable Wireless Ad Hoc Network Simulator (SWANS) and conducted simulations of Ad Hoc On-Demand Distance Vector (AODV) protocol for these as well as the random walk and random waypoint models. Our comparative results for the mobility models are discussed on a variety of simulation settings and parameters.

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Connectivity sharing for wireless mesh networks

Tesi en modalitat de cotutela: Universitat Politècnica de Catalunya i Katholieke Universiteit LeuvenInternet access is still unavailable to one-third of the world population due to the lack of infrastructure, high cost, and the digital divide. Many access-limited communities opt for shared Internet access where they build common network infrastructures to mitigate the cost. Internet connectivity in such infrastructures is typically provided by several limited, sometimes non-dedicated, gateways. Client nodes, i.e., the end-user hosts, use one gateway and switch to another when the first fails. In this scheme, the gateway configuration is done manually on the end-user side. This form of Internet connectivity is widespread and has the advantage that no central control is required, but it is also unreliable and inefficient due to several factors, such as unbalanced traffic load across the gateways. There is no doubt that the network would benefit from a gateway selection mechanism that can provide good connectivity to the client node as well as balanced load distribution and a dynamic adaptation to the current network state. However, providing such a dynamic gateway selection is complicated: since the perceived performance of the gateways changes frequently and might depend on the location of the client node in the network, and optimal selection would require the continuous monitoring of the gateway performance by the client node. The cost of such network-wide performance monitoring is high in large-scale networks and can outweigh the benefits of the dynamic gateway selection. The thesis's goal is to design a low-cost, distributed mechanism that provides an efficient and dynamic gateway selection while considering the overall balanced gateway selection distribution. To this end, we have split the problem of gateway selection into different sub-problems. First, we focus on reducing the cost of gateway performance monitoring. We propose an approach to reduce the number of monitoring requests generated by each node and analyze its effect on the gateway selection. Then, we present a collaborative monitoring method that allows neighbor nodes to share the load of the gateway monitoring. We show that every node can carry out the necessary tasks: performance monitoring, collaboration with its neighbors, and fault tolerance measures, with little computation and communication overhead. Second, to improve the gateway selection, we focus on making a selection decision that fulfills the individual performance requirements of the client nodes as well as global load balancing requirements. The solutions developed by us for the different sub-problems are embedded into a general and extensible, layered framework for gateway selection that we have called the Sense-Share-Select framework. Experimental validation and comparison with existing methods show that our framework provides accurate collaborative performance monitoring, improves the QoE for the nodes, and distributes the client nodes over the gateways in a balanced manner. The simplicity and flexibility of the framework make it adaptable to other network domains such as IoT networks and other scenarios where resource monitoring and load balancing are required.El acceso a Internet aún no está disponible para un tercio de la población mundial debido a la falta de infraestructuras, el alto costo y la brecha digital. Muchas comunidades con acceso limitado optan por el acceso compartido a Internet donde construyen infraestructuras de red comunitaria para mitigar el costo. La conectividad a Internet en dichas infraestructuras suele estar a cargo de varias puerta de enlaces limitadas en recursos, y a veces no dedicadas. Los nodos de cliente, es decir, los hosts de usuario final, utilizan una puerta de enlace y cambian a otra cuando falla la primera. En este esquema, la configuración de la puerta de enlace se realiza manualmente en el lado del usuario final. Esta forma de conectividad a Internet está muy extendida y tiene la ventaja de que no se requiere un control central, pero tampoco es confiable y eficiente debido a varios factores, como una carga desequilibrada de tráfico a través de las puertas de enlace. No hay duda de que la red se beneficiaría de un mecanismo de selección de pasarela que pueda proporcionar una buena conectividad al nodo cliente, así como una distribución equilibrada de la carga y una adaptación dinámica al estado actual de la red. Sin embargo, proporcionar una selección de puerta de enlace tan dinámica es complicado: dado que el rendimiento percibido de las puertas de enlace cambia con frecuencia y podría depender de la ubicación del nodo cliente en la red, y la selección óptima requeriría la supervisión continua del rendimiento de la puerta de enlace por parte del nodo cliente. El costo de dicha supervisión del rendimiento en toda la red es muy alto en redes de gran escala y puede superar los beneficios de la selección de puerta de enlace dinámica. El objetivo de la tesis es diseñar un mecanismo distribuido de bajo costo que proporcione una selección de puerta de enlace dinámica y eficiente al tiempo que considera la distribución general de selección de puerta de enlace equilibrada. Con este fin, hemos dividido el problema de la selección de la puerta de enlace en diferentes subproblemas. Primero, nos enfocamos en reducir el coste del monitoreo del rendimiento de la puerta de enlace. Proponemos un enfoque para reducir la cantidad de solicitudes de monitoreo generadas por cada nodo y analizar su efecto en la selección de la puerta de enlace. Luego, presentamos un método de monitoreo colaborativo que permite a los nodos vecinos compartir la carga del monitoreo de la puerta de enlace. Demostramos que cada nodo puede realizar las tareas necesarias: monitoreo del rendimiento, colaboración con sus vecinos y medidas de tolerancia a fallas, con poca sobrecarga de cómputo y comunicación. En segundo lugar, para mejorar la selección de la puerta de enlace, nos centramos en tomar una decisión de selección que cumpla con los requisitos de rendimiento individuales de los nodos del cliente, así como con los requisitos de equilibrio de carga global. Las soluciones desarrolladas por nosotros para los diferentes subproblemas están integradas en un marco general y extensible en capas para la selección de puertas de enlace que hemos llamado el marco Sense-Share-Select. La validación experimental y la comparación con los métodos existentes muestran que nuestro marco proporciona un monitoreo de rendimiento colaborativo preciso, mejora la QoE para los nodos y distribuye los nodos del cliente a través de las puertas de enlace de manera equilibrada. La simplicidad y flexibilidad del marco lo hacen adaptable a otros dominios de red, como las redes de IoT y otros escenarios donde se requiere monitoreo de recursos y equilibrio de carga.Postprint (published version

Performance assessment of real-time data management on wireless sensor networks

Technological advances in recent years have allowed the maturity of Wireless Sensor Networks (WSNs), which aim at performing environmental monitoring and data collection. This sort of network is composed of hundreds, thousands or probably even millions of tiny smart computers known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and the requirements of low-cost nodes, these sensor node resources such as processing power, storage and especially energy are very limited. Once the sensors perform their measurements from the environment, the problem of data storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going interaction between sensors and environment results huge amounts of data. Techniques for data storage and query in WSN can be based on either external storage or local storage. The external storage, called warehousing approach, is a centralized system on which the data gathered by the sensors are periodically sent to a central database server where user queries are processed. The local storage, in the other hand called distributed approach, exploits the capabilities of sensors calculation and the sensors act as local databases. The data is stored in a central database server and in the devices themselves, enabling one to query both. The WSNs are used in a wide variety of applications, which may perform certain operations on collected sensor data. However, for certain applications, such as real-time applications, the sensor data must closely reflect the current state of the targeted environment. However, the environment changes constantly and the data is collected in discreet moments of time. As such, the collected data has a temporal validity, and as time advances, it becomes less accurate, until it does not reflect the state of the environment any longer. Thus, these applications must query and analyze the data in a bounded time in order to make decisions and to react efficiently, such as industrial automation, aviation, sensors network, and so on. In this context, the design of efficient real-time data management solutions is necessary to deal with both time constraints and energy consumption. This thesis studies the real-time data management techniques for WSNs. It particularly it focuses on the study of the challenges in handling real-time data storage and query for WSNs and on the efficient real-time data management solutions for WSNs. First, the main specifications of real-time data management are identified and the available real-time data management solutions for WSNs in the literature are presented. Secondly, in order to provide an energy-efficient real-time data management solution, the techniques used to manage data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many research works argue that the distributed approach is the most energy-efficient way of managing data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the network. Thirdly, based on these two studies and considering the complexity of developing, testing, and debugging this kind of complex system, a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach and its implementation are proposed. This will help to explore various solutions of real-time database techniques on WSNs before deployment for economizing money and time. Moreover, one may improve the proposed model by adding the simulation of protocols or place part of this simulator on another available simulator. For validating the model, a case study considering real-time constraints as well as energy constraints is discussed. Fourth, a new architecture that combines statistical modeling techniques with the distributed approach and a query processing algorithm to optimize the real-time user query processing are proposed. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world data sets as well as synthetic data sets demonstrate that the proposed solution optimizes the real-time query processing to save more energy while meeting low latency.Fundação para a Ciência e Tecnologi

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Hardware and software fingerprinting of mobile devices

This dissertation presents novel and practical algorithms to identify the software and hardware components on mobile devices. In particular, we make significant contributions in two challenging areas: library fingerprinting, to identify third-party software libraries, and device fingerprinting, to identify individual hardware components. Our work has significant implications for the privacy and security of mobile platforms. Software-based library fingerprinting can be used to detect vulnerable libraries and uncover large-scale data collection activities. We develop a novel Android library finger-printing tool, LibID, to reliably identify specific versions of in-app third-party libraries. LibID is more effective against code obfuscation than prior art. When comparing LibID with other tools in identifying the correct library version using obfuscated F-Droid apps, LibID achieves an F1 score of more than 0.5 in all cases while prior work is below 0.25. We also demonstrate the utility of LibID by detecting the use of a vulnerable version of the OkHttp library in nearly 10% of the 3 958 popular apps on the Google Play Store. Hardware-based device fingerprinting allows apps and websites to invade user privacy by tracking user activity online as the user moves between apps or websites. In particular, we present a new type of device fingerprinting attack, the factory calibration fingerprinting attack, that recovers embedded per-device factory calibration data from motion sensors in a smartphone. We investigate the calibration behaviour of each sensor and show that the calibration fingerprint is fast to generate, does not change over time or after a factory reset, and can be obtained without any special user permissions. We estimate the entropy of the calibration fingerprint and find the fingerprint is very likely to be globally unique for iOS devices (~67 bits of entropy for iPhone 6S) and recent Google Pixel devices (~57 bits of entropy for Pixel 4/4 XL). By comparison, the fingerprint generated by previous work has at most 13 bits of entropy. Following our disclosures, Apple deployed a fix in iOS 12.2 and Google in Android 11. Both code obfuscation and factory calibration help to hide software and hardware idiosyncrasies from third-parties, but this dissertation demonstrates that reliable software and hardware fingerprints can still be generated given sufficient knowledge and a suitable approach. Our work has significant practical implications and can be used to improve platform security and protect user privacy.China Scholarship Council The Boeing Company Microsoft Researc

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Context-Aware Recommendation Systems in Mobile Environments

Nowadays, the huge amount of information available may easily overwhelm users when they need to take a decision that involves choosing among several options. As a solution to this problem, Recommendation Systems (RS) have emerged to offer relevant items to users. The main goal of these systems is to recommend certain items based on user preferences. Unfortunately, traditional recommendation systems do not consider the user’s context as an important dimension to ensure high-quality recommendations. Motivated by the need to incorporate contextual information during the recommendation process, Context-Aware Recommendation Systems (CARS) have emerged. However, these recent recommendation systems are not designed with mobile users in mind, where the context and the movements of the users and items may be important factors to consider when deciding which items should be recommended. Therefore, context-aware recommendation models should be able to effectively and efficiently exploit the dynamic context of the mobile user in order to offer her/him suitable recommendations and keep them up-to-date.The research area of this thesis belongs to the fields of context-aware recommendation systems and mobile computing. We focus on the following scientific problem: how could we facilitate the development of context-aware recommendation systems in mobile environments to provide users with relevant recommendations? This work is motivated by the lack of generic and flexible context-aware recommendation frameworks that consider aspects related to mobile users and mobile computing. In order to solve the identified problem, we pursue the following general goal: the design and implementation of a context-aware recommendation framework for mobile computing environments that facilitates the development of context-aware recommendation applications for mobile users. In the thesis, we contribute to bridge the gap not only between recommendation systems and context-aware computing, but also between CARS and mobile computing.<br /

Improving Vehicular ad hoc Network Protocols to Support Safety Applications in Realistic Scenarios

La convergencia de las telecomunicaciones, la informática, la tecnología inalámbrica y los sistemas de transporte, va a facilitar que nuestras carreteras y autopistas nos sirvan tanto como plataforma de transporte, como de comunicaciones. Estos cambios van a revolucionar completamente cómo y cuándo vamos a acceder a determinados servicios, comunicarnos, viajar, entretenernos, y navegar, en un futuro muy cercano. Las redes vehiculares ad hoc (vehicular ad hoc networks VANETs) son redes de comunicación inalámbricas que no requieren de ningún tipo de infraestructura, y que permiten la comunicación y conducción cooperativa entre los vehículos en la carretera. Los vehículos actúan como nodos de comunicación y transmisores, formando redes dinámicas junto a otros vehículos cercanos en entornos urbanos y autopistas. Las características especiales de las redes vehiculares favorecen el desarrollo de servicios y aplicaciones atractivas y desafiantes. En esta tesis nos centramos en las aplicaciones relacionadas con la seguridad. Específicamente, desarrollamos y evaluamos un novedoso protocol que mejora la seguridad en las carreteras. Nuestra propuesta combina el uso de información de la localización de los vehículos y las características del mapa del escenario, para mejorar la diseminación de los mensajes de alerta. En las aplicaciones de seguridad para redes vehiculares, nuestra propuesta permite reducir el problema de las tormentas de difusión, mientras que se mantiene una alta efectividad en la diseminación de los mensajes hacia los vehículos cercanos. Debido a que desplegar y evaluar redes VANET supone un gran coste y una tarea dura, la metodología basada en la simulación se muestra como una metodología alternativa a la implementación real. A diferencia de otros trabajos previos, con el fin de evaluar nuestra propuesta en un entorno realista, en nuestras simulaciones tenemos muy en cuenta tanto la movilidad de los vehículos, como la transmisión de radio en entornos urbanos, especialmente cuando los edificios interfieren en la propagación de la señal de radio. Con este propósito, desarrollamos herramientas para la simulación de VANETs más precisas y realistas, mejorando tanto la modelización de la propagación de radio, como la movilidad de los vehículos, obteniendo una solución que permite integrar mapas reales en el entorno de simulación. Finalmente, evaluamos las prestaciones de nuestro protocolo propuesto haciendo uso de nuestra plataforma de simulación mejorada, evidenciando la importancia del uso de un entorno de simulación adecuado para conseguir resultados más realistas y poder obtener conclusiones más significativas.Martínez Domínguez, FJ. (2010). Improving Vehicular ad hoc Network Protocols to Support Safety Applications in Realistic Scenarios [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/9195Palanci