This thesis tackles problems on IEEE 802.11 MAC layer, network layer and application layer, to further push the performance of wireless P2P applications in a holistic way. It contributes to the better understanding and utilization of two major IEEE 802.11 MAC features, frame aggregation and block acknowledgement, to the design and implementation of opportunistic networks on off-the-shelf hardware and proposes a document exchange protocol, including document recommendation. First, this thesis contributes a measurement study of the A-MPDU frame aggregation behavior of IEEE 802.11n in a real-world, multi-hop, indoor mesh testbed. Furthermore, this thesis presents MPDU payload adaptation (MPA) to utilize A-MPDU subframes to increase the overall throughput under bad channel conditions. MPA adapts the size of MAC protocol data units to channel conditions, to increase the throughput and lower the delay in error-prone channels. The results suggest that under erroneous conditions throughput can be maximized by limiting the MPDU size. As second major contribution, this thesis introduces Neighborhood-aware OPPortunistic networking on Smartphones (NOPPoS). NOPPoS creates an opportunistic, pocket-switched network using current generation, off-the-shelf mobile devices. As main novel feature, NOPPoS is highly responsive to node mobility due to periodic, low-energy scans of its environment, using Bluetooth Low Energy advertisements. The last major contribution is the Neighborhood Document Sharing (NDS) protocol. NDS enables users to discover and retrieve arbitrary documents shared by other users in their proximity, i.e. in the communication range of their IEEE 802.11 interface. However, IEEE 802.11 connections are only used on-demand during file transfers and indexing of files in the proximity of the user. Simulations show that NDS interconnects over 90 \% of all devices in communication range. Finally, NDS is extended by the content recommendation system User Preference-based Probability Spreading (UPPS), a graph-based approach. It integrates user-item scoring into a graph-based tag-aware item recommender system. UPPS utilizes novel formulas for affinity and similarity scoring, taking into account user-item preference in the mass diffusion of the recommender system. The presented results show that UPPS is a significant improvement to previous approaches.

This dissertation presents contributions to the fields of mobility modeling, wireless sensor networks (WSNs) with mobile sinks, and opportunistic communication in theme parks. The two main directions of our contributions are human mobility models and strategies for the mobile sink positioning and communication in wireless networks. The first direction of the dissertation is related to human mobility modeling. Modeling the movement of human subjects is important to improve the performance of wireless networks with human participants and the validation of such networks through simulations. The movements in areas such as theme parks follow specific patterns that are not taken into consideration by the general purpose mobility models. We develop two types of mobility models of theme park visitors. The first model represents the typical movement of visitors as they are visiting various attractions and landmarks of the park. The second model represents the movement of the visitors as they aim to evacuate the park after a natural or man-made disaster. The second direction focuses on the movement patterns of mobile sinks and their communication in responding to various events and incidents within the theme park. When an event occurs, the system needs to determine which mobile sink will respond to the event and its trajectory. The overall objective is to optimize the event coverage by minimizing the time needed for the chosen mobile sink to reach the incident area. We extend this work by considering the positioning problem of mobile sinks and preservation of the connected topology. We propose a new variant of p-center problem for optimal placement and communication of the mobile sinks. We provide a solution to this problem through collaborative event coverage of the WSNs with mobile sinks. Finally, we develop a network model with opportunistic communication for tracking the evacuation of theme park visitors during disasters. This model involves people with smartphones that store and carry messages. The mobile sinks are responsible for communicating with the smartphones and reaching out to the regions of the emergent events.

When in physical proximity, data can be directly exchanged between the mobile devices people carry - for example over Bluetooth. If people cooperate to store, carry and forward messages on one another's behalf, then an opportunistic network may be formed, independent of any fixed infrastructure. To enable performant routing within opportunistic networks, use of social network information has been proposed for social network routing protocols. But the decentralised and cooperative nature of the networks can however expose users of such protocols to privacy and security threats, which may in turn discourage participation in the network. In this thesis, we examine how to mitigate privacy and security threats in opportunistic networks while maintaining network performance. We first demonstrate that privacy-aware routing protocols are required in order to maintain network performance while respecting users' privacy preferences. We then demonstrate novel social network routing protocols that mitigate specific threats to privacy and security while maintaining network performance.

In urban search and rescue (USAR) operations, there is a considerable amount of danger faced by rescuers. The use of mobile robots can alleviate this issue. Coordinating the search effort is made more difficult by the communication issues typically faced in these environments, such that communication is often restricted. With small numbers of robots, it is necessary to break communication links in order to explore the entire environment. The robots can be viewed as a broken ad hoc network, relying on opportunistic contact in order to share data. In order to minimise overheads when exchanging data, a novel algorithm for data exchange has been created which maintains the propagation speed of flooding while reducing overheads. Since the rescue workers outside of the structure need to know the location of any victims, the task of finding their locations is two parted: 1) to locate the victims (Search Time), and 2) to get this data outside the structure (Delay Time). Communication with the outside is assumed to be performed by a static robot designated as the Command Station. Since it is unlikely that there will be sufficient robots to provide full communications coverage of the area, robots that discover victims are faced with the difficult decision of whether they should continue searching or return with the victim data. We investigate a variety of search techniques and see how the application of biological foraging models can help to streamline the search process, while we have also implemented an opportunistic network to ensure that data are shared whenever robots come within line of sight of each other or the Command Station. We examine this trade-off between performing a search and communicating the results.

El presente trabajo presenta el estado del arte de las redes Ad Hoc y su posible aplicación a soluciones para rescatistas y de situación de emergencia por desastres naturales o de otra índole.

L’Internet a complètement révolutionné la façon dont nous communiquons. En parallèle, la croissance importante des réseaux mobiles s'est accompagnée d'une explosion du nombre d’usagers et d'une augmentation exponentielle de la demande. Cependant, l’Internet n'est pas encore, voire n'est pas toujours, universellement accessible. Par exemple, c'est le cas en ce qui concerne l’accès dans les économies émergentes ou dans les régions éloignées, les obstacles physiques empêchant le déploiement de réseaux mobiles et les désastres naturels. C'est dans ce contexte que les réseaux tolérants au délai ont été introduits pour faire face aux environnements caractérisés par des interruptions et des délais de transmission élevés. Ces réseaux, manquent souvent de routes pré-déterminées ou même de toute infrastructure pour permettre une communication de bout-en-bout. Dans ce contexte, tous les nœuds de ces réseaux peuvent interagir en utilisant leurs contacts comme une opportunité de communication. Le paradigme stockage/transport permet à ces nœuds d’exploiter des chemins spatio-temporels créés par ces possibilités de contact afin de livrer des messages au fil du temps. Dans ce travail, nous soulevons ici une question générique : pouvons-nous concevoir une infrastructure mobile et opportuniste qui pourrait aider à transmettre ces messages ? Afin de fournir une telle infrastructure, nous étudions l’application des marches aléatoires temporelles (TRWs) dans réseaux opportunistes. Nous explorons l’application et l’impact de la TRW pour fournir une infrastructure minimale et non-invasive à partir de deux points de vue : le stockage des données et leur transmission. / The Internet has entirely reshaped the way we communicate and interact with one another. The rapid development of the wireless infrastructure by network providers has being accompanied by an exponential growth in the number of mobile users. However, global Internet access and connectivity still face several challenges: scarce or poor quality connectivity in developing countries or places with limited accessibility, physical obstacles limiting the deployment of wireless networks and natural or man-made disasters. Delay tolerant networks (DTNs) were introduced to deal with environments where interruptions or disruptions of service were expected. Such networks usually lack of end-to-end paths or any infrastructure to help communications. In these networks, mobile nodes may interact using their contacts as a communication opportunity. The store-carry-forward paradigm allows nodes to exploit spatio-temporal paths created by contact opportunities in order to deliver messages over time. Instead we raise the question: can we design a mobile and opportunistic infrastructure that could help deliver messages? In the quest to provide such infrastructure, we study the application of temporal random walks (TRW) over the opportunistic networks. We explore the application and impact of TRW as a minimal and non invasive infrastructure from two points of view: data forwarding and data recollection/transmission.

With online social networks such as Facebook and Twitter becoming globally popular, there is renewed interest in understanding the structural and dynamical properties of social networks. In this thesis we study several stochastic models arising in the context of the spread of influence or information in social networks. Our objective is to provide compact and accurate quantitative descriptions of the spread processes, to understand the effects of various system parameters, and to design policies for the control of such diffusions. One of the well established models for influence spread in social networks is the threshold model. An individual’s threshold indicates the minimum level of “influence” that must be exerted, by other members of the population engaged in some activity, before the individual will join the activity. We begin with the well-known Linear Threshold (LT) model introduced by Kempe et al. [1]. We analytically characterize the expected influence for a given initial set under the LT model, and provide an equivalent interpretation in terms of acyclic path probabilities in a Markov chain. We derive explicit optimal initial sets for some simple networks and also study the effectiveness of the Pagerank [2] algorithm for the problem of influence maximization. Using insights from our analytical characterization, we then propose a computationally efficient G1-sieving algorithm for influence maximization and show that it performs on par with the greedy algorithm, through experiments on a coauthorship dataset. The Markov chain characterisation gives only limited insights into the dynamics of influence spread and the effects of the various parameters. We next provide such insights in a restricted setting, namely that of a homogeneous version of the LT model but with a general threshold distribution, by taking the fluid limit of a probabilistically scaled version of the spread Markov process. We observe that the threshold distribution features in the fluid limit via its hazard function. We study the effect of various threshold distributions and show that the influence evolution can exhibit qualitatively different behaviors, depending on the threshold distribution, even in a homogeneous setting. We show that under the exponential threshold distribution, the LT model becomes equivalent to the SIR (Susceptible-Infected-Recovered) epidemic model [3]. We also show how our approach is easily amenable to networks with heterogeneous community structures. Hundreds of millions of people today interact with social networks via their mobile devices. If the peer-to-peer radios on such devices are used, then influence spread and information spread can take place opportunistically when pairs of such devices come in proximity. In this context, we develop a framework for content delivery in mobile opportunistic networks with joint evolution of content popularity and availability. We model the evolution of influence and content spread using a multi-layer controlled epidemic model, and, using the monotonicity properties of the o.d.e.s, prove that a time-threshold policy for copying to relay nodes is delay-cost optimal. Information spread occurs seldom in isolation on online social networks. Several contents might spread simultaneously, competing for the common resource of user attention. Hence, we turn our attention to the study of competition between content creators for a common population, across multiple social networks, as a non-cooperative game. We characterize the best response function, and observe that it has a threshold structure. We obtain the Nash equilibria and study the effect of cost parameters on the equilibrium budget allocation by the content creators. Another key aspect to capturing competition between contents, is to understand how a single end-user receives and processes content. Most social networks’ interface involves a timeline, a reverse chronological list of contents displayed to the user, similar to an email inbox. We study competition between content creators for visibility on a social network user’s timeline. We study a non-cooperative game among content creators over timelines of fixed size, show that the equilibrium rate of operation under a symmetric setting, exhibits a non-monotonic behavior with increasing number of players. We then consider timelines of infinite size, along with a behavioral model for user’s scanning behavior, while also accounting for variability in quality (influence weight) among content creators. We obtain integral equations, that capture the evolution of average influence of competing contents on a social network user’s timeline, and study various content competition formulations involving quality and quantity.

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

Les réseaux opportunistes (DTN) permettent d'utiliser de nouveaux vecteurs de transmissions. Avant de pouvoir profiter de toutes les capacités des DTN, nous devons nous pencher sur la compréhension de ce nouveau paradigme. De nombreuses propriétés des réseaux DTN sont maintenant reconnues, cependant les relations entre un noeud du réseau et son voisinage proche ne semblent pas encore avoir été passée au crible. Souvent, la présence de noeuds voisins proches mais pas directement lié par le contact est ignorée. Dans cette thèse, nous montrons à quel point considérer les noeuds à proximité nous aide à améliorer les performances DTNs.En identifiant le paradoxe binaire dans les DTN, nous montrons que les caractérisations actuelles ne sont pas suffisantes pour bénéficier de toutes les possibilités de transmission dans les DTN. Nous proposons une définition formelle du voisinage pour les DTNs avec le ``k-vicinity''. Nous étudions les caractérisations temporelles du k-vicinity avec différentes données. Ensuite, nous nous concentrons sur l'étude de l'organisation interne du k-vicinity. Nous avons crée le Vicinity Motion qui permet d'obtenir un modèle markovien à partir de n'importe quelle trace de contact. Nous en extrayions trois mouvements principaux: la naissance, la mort et les mouvements séquentiels. Grâce aux valeurs du Vicinity Motion, nous avons pu créer un générateur synthétique de mouvements de proximité nommé TiGeR. Enfin, nous posons la question de la prévisibilité des distances entre deux noeuds du k-vicinity. En utilisant le savoir emmagasiné dans le Vicinity Motion, nous mettons au point une heuristique permettant de prédire les futures distances entre deux noeuds. / The networking paradigm uses new information vectors consisting of human carried devices is known as disruption-tolerant networks (DTN) or opportunistic networks. We identify the binary assertion issue in DTN. We notice how most DTNs mainly analyze nodes that are in contact. So all nodes that are not in contact are in intercontact. Nevertheless, when two nodes are not in contact, this does not mean that they are topologically far away from one another. We propose a formal definition of vicinities in DTNs and study the new resulting contact/intercontact temporal characterization. Then, we examine the internal organization of vicinities using the Vicinity Motion framework. We highlight movement types such as birth, death, and sequential moves. We analyze a number of their characteristics and extract vicinity usage directions for mobile networks. Based on the vicinity motion outputs and extracted directions, we build the TiGeR that simulates how pairs of nodes interact within their vicinities. Finally, we inquire about the possibilities of vicinity movement prediction in opportunistic networks. We expose a Vicinity Motion-based heuristic for pairwise shortest distance forecasting. We use two Vicinity Motion variants called AVM and SVM to collect vicinity information. We find that both heuristics perform quite well with performances up to 99% for SVM and around 40% for AVM.

Location-sharing services have become increasingly popular with the proliferation of smartphones and online social networks. People share their locations with each other to record their daily lives or satisfy their social needs. At the same time, inappropriate disclosure of location information poses threats to people's privacy. One of the reasons why people fail to protect their location privacy is the difficulty of using the current mechanisms to manually configure location-privacy settings. Since people's location-privacy preferences are context-aware, manual configuration is cumbersome. People's incapability and unwillingness to do so lead to unexpected location disclosures that violate their location privacy. In this thesis, we investigate the feasibility of using recommender systems to help people protect their location privacy. We examine the performance of location-privacy recommender systems and compare it with the state-of-the-art. We also conduct online user studies to understand people's acceptance of such recommender systems and their concerns. We revise our design of the systems according to the results of the user studies. We find that user-based collaborative filtering can accurately recommend location-privacy preferences and outperform the state-of-the-art when training data are insufficient. From users' perspective, their acceptance of location-privacy recommender systems is affected by the openness and the context of recommendations and their privacy concerns about the systems. It is feasible to use data obfuscation or decentralisation to alleviate people's concerns and meanwhile keep the systems robust against malicious data attacks.