Teses / dissertações sobre o tema "Dynamic link networks"

À mesure que la demande de services interactifs, de multimédia et de capacités de réseau augmente dans les réseaux modernes, de nouveaux logiciels et/ou composants matériels devraient être intégrés. Par conséquent, le processus d'évaluation et de validation de ces nouvelles solutions est essentiel pour déterminer si elles sont performantes, fiables et robustes avant d'être déployées dans un réseau réel. L'émulation de réseau est de plus en plus utilisée pour répliquer le comportement de réseau réel à faible coût d'infrastructure et avec un niveau de réalisme plus élevé que les simulations. Cette approche permet de tester en continu la solution finale sans nécessiter de modifications après le déploiement. Cependant, l'émulation de réseaux avec des paramètres de liaison qui peuvent changer au fil du temps en raison de facteurs internes et externes, comme dans les communications par satellite, complique l'architecture d'émulation, faisant des tests exhaustifs dans diverses conditions une tâche difficile. De plus, s'assurer que l'émulateur est adéquat pour le contexte donné et qu'il est conçu correctement est crucial pour obtenir des résultats fiables. Cela inclut la vérification que l'émulateur peut répliquer avec précision les conditions et les scénarios spécifiques du réseau pour lesquels il est destiné. Dans cette thèse, nous abordons les défis de l'émulation et de la validation des réseaux à liens dynamiques. Nous proposons un modèle pour ce type de réseaux et leurs paramètres, en tenant compte des limitations dans la description et l'exécution du comportement dynamique. Nous avons développé une plateforme d'émulation qui intègre notre modèle proposé et permet de tester et d'évaluer différents scénarios de réseau dans un environnement contrôlé. Pour assurer une émulation correcte et combler l'écart entre l'émulation et les scénarios réels, la vérification de modèle et la vérification d'exécution ont été proposées. De plus, l'exécution de l'émulation a été vérifiée en extrayant un jeu de données de paramètres réseau et en vérifiant qu'il respecte certaines propriétés d'intérêt au fil du temps. Enfin, nous introduisons une nouvelle méthode utilisant le modèle d'automate cellulaire pour simuler avec précision l'évolution des paramètres du réseau en garantissant que certaines propriétés soient maintenues pendant cette évolution, de sorte qu'il est possible de les transférer rapidement vers une configuration d'émulation où les paramètres du réseau atteignent des valeurs critiques
As the demand for interactive services, multimedia, and network capabilities grows in modern networks, novel software and/or hardware components should be incorporated. As a consequence, the assessment and validation process of these newly developed solutions is critical to determining whether they perform well, are reliable, and are robust before being deployed in a real network.Network emulation is increasingly used to replicate real-world network behavior at low infrastructure costs and with a higher level of realism than simulations. This approach allows for continuous testing of the final solution without requiring changes after deployment. However, emulating networks with link parameters that may change over time due to internal and external factors, as in satellite communications, complicates the emulation architecture, making thorough testing under various conditions a challenging task. Moreover, ensuring that the emulator is adequate for the given context and is designed correctly is crucial for obtaining reliable results. This includes verifying that the emulator can accurately replicate the specific network conditions and scenarios for which it is intended.In this thesis, we address the challenges of dynamic-link network emulation and validation. We propose a model for dynamic-link networks and their parameters, considering the limitations in describing and executing dynamic behavior. We have developed an emulation platform that incorporates our proposed model and allows to test and evaluate various network scenarios in a controlled environment. To ensure proper emulation and bridge the gap between emulation and real-world scenarios, both model checking and run-time verification have been proposed. Additionally, the emulation execution has been verified by extracting a dataset of network parameters and checking it respects certain properties of interest over time. Finally, we have introduced a novel method using the Cellular Automaton model to accurately simulate the evolution of network parameters while ensuring that certain properties are maintained throughout this evolution, thereby potentially fast transfer to an emulation configuration where network parameters reach critical values

Thesis (MSc (Mathematical Sciences. Computer Science))--University of Stellenbosch, 2009.
ENGLISH ABSTRACT: Since 2002 data tra c has overtaken voice tra c in volume [1]. Telecom / Network operators still generate most of their income carrying voice tra c. There is however a huge revenue potential in delivering reliable guaranteed data services. Network survivability and recovery from network failures are integral to network reliability. Due to the nature of the Internet, recovery from link failures needs to be distributed and dynamic in order to be scalable. Link failure recovery schemes are evaluated in terms of the survivability of the network, the optimal use of network resources, scalability, and the recovery time of such schemes. The need for recovery time to be improved is highlighted by real-time data tra c such as VoIP and video services carried over the Internet. The goal of this thesis is to examine existing link failure recovery schemes and evaluate the need for their extension, and to evaluate the performance of the proposed link failure recovery schemes. i
AFRIKAANSE OPSOMMING: Sedert 2002 het data verkeer die stem verkeer in volume verbygesteek [1]. Telekommunikasie / netwerk operateurs genereer egter steeds die meeste van hul inkomste met stem verkeer. Netwerk oorlewing en die herstel van netwerk mislukkings is integraal tot netwerk stabiliteit. Die samestelling van die Internet noodsaak dat die herstel van skakel mislukkings verspreid en dinamies van natuur moet wees. Die herstel-skema van skakel mislukkings word evalueer in terme van die oorleefbaarheid van die netwerk, die mees e ektiewe benutting van network bronne, aanpasbaarheid, en die herstel tydperk van die skema. Die vinnig moontlikste herstel tydperk word genoodsaak deur oombliklike data verkeer soos VoIP en beeld dienste wat oor die Internet gedra word. The doel van hierdie tesis is om bestaande skakel mislukking herstel skemas te evalueer, en dan verder ondersoek in te stel na hul uitbreiding. Daarna word die voorgestelde skakel mislukking skema se e ektiwiteit gemeet.

During the last years, we have observed a progressive and continuous expansion of human-centered mobile wireless networks. The advent of these networks has encouraged the researchers to think about new solutions in order to ensure efficient evaluation and design of communication protocols. In fact, these networks are faced to several constraints as the lack of infrastructure, the dynamic topology, the limited resources and the deficient quality of service and security. We have been interested in the dynamicity of the network and in particular in human mobility. The human mobility has been widely studied in order to extract its intrinsic properties and to harness them to propose more accurate approaches. Among the prominent properties depicted in the literature, we have been specially attracted by the impact of the social interactions on the human mobility and consequently on the structure of the network. To grasp structural information of such networks, many metrics and techniques have been borrowed from the Social Network Analysis (SNA). The SNA can be seen as another network measurement task which extracts structural information of the network and provides useful feedback for communication protocols. In this context, the SNA has been extensively used to perform link prediction in social networks relying on their structural properties. Motivated by the importance of social ties in human-centered mobile wireless networks and by the possibilities that are brought by SNA to perform link prediction, we are interested by designing the first link prediction framework adapted for mobile wireless networks as Mobile Ad-hoc Networks (MANETs) and Delay/Disruption Tolerant Networks (DTN). Our proposal tracks the evolution of the network through a third-order tensor over T periods and computes the sociometric Katz measure for each pair of nodes to quantify the strength of the social ties between the network entities. Such quantification gives insights about the links that are expected to occur in the period T+1 and the new links that are created in the future without being observed during the tracking time. To attest the efficiency of our framework, we apply our link prediction technique on three real traces and we compare its performance to the ones of other well-known link prediction approaches. The results prove that our method reaches the highest level of accuracy and outperforms the other techniques. One of the major contributions behind our proposal highlights that the link prediction in such networks can be made in a distributed way. In other words, the nodes can predict their future links relying on the local information (one-hop and two-hop neighbors) instead of a full knowledge about the topology of the network. Furthermore, we are keen to improve the link prediction performance of our tensor-based framework. To quantify the social closeness between the users, we take into consideration two aspects of the relationships: the recentness of the interactions and their frequency. From this perspective, we wonder if we can consider a third criterion to improve the link prediction precision. Asserting the heuristic that stipulates that persistent links are highly predictable, we take into account the stability of the relationships (link and proximity stabilities). To measure it, we opt for the entropy estimation of a time series proposed in the Lempel-Ziv data compression algorithm. As we think that our framework measurements and the stability estimations complement each other, we combine them in order to provide new link prediction metrics. The simulation results emphasize the pertinence of our intuition. Providing a tensor-based link prediction framework and proposing relative enhancements tied to stability considerations represent the main contributions of this thesis. Along the thesis, our concern was also focused on mechanisms and metrics that contribute towards improving communication protocols in these mobile networks [...]

Durant ces dernières années, nous avons observe une expansion progressive et continue des réseaux mobile sans-fil centres sur l’être humain. L’apparition de ces réseaux a encouragé les chercheurs à réfléchir à de nouvelles solutions pour assurer une évaluation efficace et une conception adéquate des protocoles de communication. En effet, ces réseaux sont sujets à de multiples contraintes telles que le manque d’infrastructure, la topologie dynamique, les ressources limitées ainsi que la qualité de service et la sécurité des informations précaires. Nous nous sommes spécialement intéressés à l’aspect dynamique du réseau et en particulier à la mobilité humaine. La mobilité humaine a été largement étudiée pour pouvoir extraire ses propriétés intrinsèques et les exploiter pour des approches plus adaptées à cette mobilité. Parmi les propriétés les plus intéressantes soulevées dans la littérature, nous nous sommes focalisés sur l’impact des interactions sociales entre les entités du réseau sur la mobilité humaine et en conséquence sur la structure du réseau. Pour recueillir des informations structurelles sur le réseau, plusieurs métriques et techniques ont été empruntées de l’analyse des réseaux sociaux (SNA). Cet outil peut être assimilé à une autre alternative pour mesurer des indicateurs de performance du réseau. Plus précisément, il extrait des informations structurelles du réseau et permet aux protocoles de communication de bénéficier d’indications utiles telles que la robustesse du réseau, les nœuds centraux ou encore les communautés émergentes. Dans ce contexte, la SNA a été largement utilisée pour prédire les liens dans les réseaux sociaux en se basant notamment sur les informations structurelles. Motivés par l’importance des liens sociaux dans les réseaux mobiles sans-fil centres sur l’être humain et par les possibilités offertes par la SNA pour prédire les liens, nous nous proposons de concevoir la première méthode capable de prédire les liens dans les réseaux sans-fil mobiles tels que les réseaux ad-hoc mobiles (MANETs) et les réseaux tolérants aux délais (DTNs). Notre proposition suit l’évolution de la topologie du réseau sur T périodes à travers un tenseur (en ensemble de matrices d’adjacence et chacune des matrices correspond aux contacts observés durant une période bien spécifique). Ensuite, elle s’appuie sur le calcul de la mesure sociométrique de Katz pour chaque paire de nœuds pour mesurer l’étendue des relations sociales entre les différentes entités du réseau. Une telle quantification donne un aperçu sur les liens dont l’occurrence est fortement pressentie à la période T+1 et les nouveaux liens qui se créent dans le futur sans pour autant avoir été observés durant le temps de suivi. Pour attester l’efficacité de notre proposition, nous l’appliquons sur trois traces réelles et nous comparons sa performance à celles d’autres techniques de prédiction de liens présentées dans la littérature. Les résultats prouvent que notre méthode est capable d’atteindre le meilleur niveau d’efficacité et sa performance surpasse celles des autres techniques. L’une des majeures contributions apportées par cette proposition met en exergue la possibilité de prédire les liens d’une manière décentralisée. En d’autres termes, les nœuds sont capables de prédire leurs propres liens dans le futur en se basant seulement sur la connaissance du voisinage immédiat (voisins à un et deux sauts). En outre, nous sommes désireux d’améliorer encore plus la performance de notre méthode de prédiction de liens. Pour quantifier la force des relations sociales entre les entités du réseau, nous considérons deux aspects dans les relations : la récence des interactions et leur fréquence. À partir de là, nous nous demandons s’il est possible de prendre en compte un troisième critère pour améliorer la précision des prédictions […]
During the last years, we have observed a progressive and continuous expansion of human-centered mobile wireless networks. The advent of these networks has encouraged the researchers to think about new solutions in order to ensure efficient evaluation and design of communication protocols. In fact, these networks are faced to several constraints as the lack of infrastructure, the dynamic topology, the limited resources and the deficient quality of service and security. We have been interested in the dynamicity of the network and in particular in human mobility. The human mobility has been widely studied in order to extract its intrinsic properties and to harness them to propose more accurate approaches. Among the prominent properties depicted in the literature, we have been specially attracted by the impact of the social interactions on the human mobility and consequently on the structure of the network. To grasp structural information of such networks, many metrics and techniques have been borrowed from the Social Network Analysis (SNA). The SNA can be seen as another network measurement task which extracts structural information of the network and provides useful feedback for communication protocols. In this context, the SNA has been extensively used to perform link prediction in social networks relying on their structural properties. Motivated by the importance of social ties in human-centered mobile wireless networks and by the possibilities that are brought by SNA to perform link prediction, we are interested by designing the first link prediction framework adapted for mobile wireless networks as Mobile Ad-hoc Networks (MANETs) and Delay/Disruption Tolerant Networks (DTN). Our proposal tracks the evolution of the network through a third-order tensor over T periods and computes the sociometric Katz measure for each pair of nodes to quantify the strength of the social ties between the network entities. Such quantification gives insights about the links that are expected to occur in the period T+1 and the new links that are created in the future without being observed during the tracking time. To attest the efficiency of our framework, we apply our link prediction technique on three real traces and we compare its performance to the ones of other well-known link prediction approaches. The results prove that our method reaches the highest level of accuracy and outperforms the other techniques. One of the major contributions behind our proposal highlights that the link prediction in such networks can be made in a distributed way. In other words, the nodes can predict their future links relying on the local information (one-hop and two-hop neighbors) instead of a full knowledge about the topology of the network. Furthermore, we are keen to improve the link prediction performance of our tensor-based framework. To quantify the social closeness between the users, we take into consideration two aspects of the relationships: the recentness of the interactions and their frequency. From this perspective, we wonder if we can consider a third criterion to improve the link prediction precision. Asserting the heuristic that stipulates that persistent links are highly predictable, we take into account the stability of the relationships (link and proximity stabilities). To measure it, we opt for the entropy estimation of a time series proposed in the Lempel-Ziv data compression algorithm. As we think that our framework measurements and the stability estimations complement each other, we combine them in order to provide new link prediction metrics. The simulation results emphasize the pertinence of our intuition. Providing a tensor-based link prediction framework and proposing relative enhancements tied to stability considerations represent the main contributions of this thesis. Along the thesis, our concern was also focused on mechanisms and metrics that contribute towards improving communication protocols in these mobile networks […]

El crecimiento de la potencia de procesamiento de los sistemas de computación paralelos requiere redes de interconexión de mayor nivel de complejidad y un mayor rendimiento, por lo que consumen más energía. Mayor cantidad de energía consumida conduce a muchos problemas relacionados con los costos, la infraestructura y la estabilidad del sistema de refrigeración. Los enlaces de la red contribuyen en una proporción sustancial al consumo total de energía de dichas redes. Varias propuestas se han ido acercando a una mejor administración de la energía de los enlaces. En esta tesis, aprovechamos ciertas características integradas en la tecnología actual de los enlaces para ajustar dinámicamente la velocidad de los mismos en función del tráfico. De esta manera, la red de interconexión consume menos energía cuando el tráfico es ligero. También proponemos una política de enrutamiento que tiene en cuenta la velocidad del enlace que favorece las conexiones de alta velocidad en el proceso de enrutamiento de paquetes para aumentar el rendimiento de la red cuando se despliega el mecanismo de ahorro de energía. Los resultados de la evaluación muestran que las redes que usan el mecanismo de ahorro de energía aquí propuesto, reducen el consumo de energía a expensas de un aumento en el promedio de latencia de paquetes. Sin embargo, con la propuesta de política de enrutamiento que tiene en cuenta la velocidad del enlace, nuestro mecanismo incurre en un menor aumento en el promedio de la latencia de paquetes mientras se logra un ahorro de energía similar, en comparación con otros enfoques convencionales de la literatura.
The growing processing power of parallel computing systems requires interconnection networks a higher level of complexity and higher performance, thus they consume more energy. A larger amount of energy consumed leads to many problems related to cost, cooling infrastructure and system stability. Link components contribute a substantial proportion of the total energy consumption of the networks. Several proposals have been approaching a better link power management. In this thesis, we leverage built-in features of current link technology to dynamically adjust the link speed as a function of traffic. By doing this, the interconnection network consumes less energy when traffic is light. We also propose a link speed aware routing policy that favors high-speed links in the process of routing packets to boost the performance of the network when the energy saving mechanism is deployed. The evaluation results show that the networks deploying our energy saving mechanism reduce the amount of energy consumption with the expense of an increase in the average packet latency. However, with the link speed aware routing policy proposal, our mechanism incurs a less increase in the average packet latency while achieving similar energy saving, compared with other conventional approaches in literature.

Topological evolution over time in a dynamic network triggers both the addition and deletion of actors and the links among them. A dynamic network can be represented as a time series of network snapshots where each snapshot represents the state of the network over an interval of time (for example, a minute, hour or day). The duration of each snapshot denotes the temporal scale/sliding window of the dynamic network and all the links within the duration of the window are aggregated together irrespective of their order in time. The inherent trade-off in selecting the timescale in analysing dynamic networks is that choosing a short temporal window may lead to chaotic changes in network topology and measures (for example, the actors’ centrality measures and the average path length); however, choosing a long window may compromise the study and the investigation of network dynamics. Therefore, to facilitate the analysis and understand different patterns of actor-oriented evolutionary aspects, it is necessary to define an optimal window length (temporal duration) with which to sample a dynamic network. In addition to determining the optical temporal duration, another key task for understanding the dynamics of evolving networks is being able to predict the likelihood of future links among pairs of actors given the existing states of link structure at present time. This phenomenon is known as the link prediction problem in network science. Instead of considering a static state of a network where the associated topology does not change, dynamic link prediction attempts to predict emerging links by considering different types of historical/temporal information, for example the different types of temporal evolutions experienced by the actors in a dynamic network due to the topological evolution over time, known as actor dynamicities. Although there has been some success in developing various methodologies and metrics for the purpose of dynamic link prediction, mining actor-oriented evolutions to address this problem has received little attention from the research community. In addition to this, the existing methodologies were developed without considering the sampling window size of the dynamic network, even though the sampling duration has a large impact on mining the network dynamics of an evolutionary network. Therefore, although the principal focus of this thesis is link prediction in dynamic networks, the optimal sampling window determination was also considered.

Le TDD dynamique joue un rôle crucial dans les réseaux 5G, adaptant les ressources aux besoins variés. Il améliore l'efficacité spectrale en allouant dynamiquement des créneaux horaires pour les transmissions montantes et descendantes en fonction de la demande de trafic et des conditions de canal. Cette allocation dynamique de fréquence assure une utilisation efficace du spectre et prend en charge une connectivité massive, une latence faible et les exigences de la qualité de service. Son rôle dans l'agrégation de porteuses maximise les débits de données et la capacité du réseau, soulignant son importance dans les technologies de communication sans fil avancées.Cependant, le TDD dynamique est confronté à un défi majeur : l'Interférence des liens croisés. Ce type d'interférence se produit lorsque les transmissions montantes et descendantes partagent les mêmes bandes de fréquences, provoquant des interférences.Cette interférence comprend l'interférence de Station de Base à Station de Base (BS-to-BS) ou du lien descendant au lien montant (DL-to-UL) ainsi que l'interférence d'Équipement Utilisateur à Équipement Utilisateur (UE-to-UE) ou du lien montant vers le lien descendant (UL- to-DL). Dans l'interférence DL-to-UL, les transmissions descendantes débordent dans les bandes des transmissions montantes, dégradant la communication montante. À l'inverse, l'interférence UL-to-DL se produit lorsque les transmissions montantes interfèrent avec la réception des transmissions descendantes.Gérer efficacement ces interférences est crucial pour la performance et la fiabilité d'un système TDD dynamique.Ce mémoire vise à libérer tout le potentiel du TDD dynamique en surmontant les défis posés par les interférences des liens croisés grâce à une analyse rigoureuse et des méthodologies innovantes. La recherche ne se contente pas de faire progresser la technologie TDD dynamique, elle pionnière des solutions applicables à divers contextes de communication, stimulant des stratégies innovantes d'alignement d'interférence dans des scénarios variés.Le mémoire se divise en plusieurs parties. La première pose les bases avec la définition du problème et les concepts théoriques essentiels. La deuxième partie examine les conditions de faisabilité de l'alignement des interférences. Ces conditions sont exprimées en fonction de la dimension du problème et établissent le degré de liberté (DoF) atteignable, représentant le nombre de flux de données possibles. Elle explore l'alignement d'interférence dans des scénarios centralisés, en considérant à la fois les canaux MIMO en rang complet et réduit, et aborde des complexités du monde réel. De plus, elle étend l'exploration à un scénario distribué, offrant une compréhension réaliste des complexités de la communication. La troisième partie se concentre sur les techniques d'optimisation, en particulier le beamforming. Elle introduit le Zero Forcing (ZF) beamforming pour les utilisateurs, alignant l'interférence dans les systèmes TDD dynamique. Elle met l'accent sur l'impact de l'interférence des liens croisés entre utilisateurs et présente les améliorations apportées par les algorithmes WMMSE. De plus, elle explore l'optimisation de l'allocation de puissance en utilisant l'algorithme Water-Filling, évaluant la performance du Zero Forcing Beamforming et de l'algorithme WMMSE en fonction de cette approche d'optimisation de puissance
Dynamic Time Division Duplexing (DynTDD) is pivotal in 5th generation (5G) networks, adapting resources to diverse needs. It enhances Spectral Efficiency (SE) by dynamically allocating time slots for Uplink (UL) and Downlink (DL) transmissions based on traffic demand and channel conditions. This dynamic frequency allocation ensures efficient spectrum use and supports massive connectivity, low latency, and Quality-of-Service (QoS) requirements. Its role in carrier aggregation maximizes data rates and capacity, highlighting its importance in advanced wireless communication technologies.However, DynTDD faces a significant challenge: cross-link interference (CLI). CLI occurs when UL and DL transmissions share the same frequency bands, leading to interference.CLI comprises base station to base station (BS-to-BS) or downlink to uplink (DL-to-UL) interference and user equipment to user equipment (UE-to-UE) or uplink to downlink (UL-to-DL) interference. In DL-to-UL interference, DL transmissions spill into UL bands, degrading UL communication. Conversely, UL-to-DL interference occurs when UL transmissions interfere with DL reception.Effectively managing CLI is crucial for DynTDD's performance and reliability.This thesis aims to unleash the full potential of DynTDD by overcoming CLI challenges through rigorous analysis and innovative methodologies. The research not only advances DynTDD technology but also pioneers solutions applicable to various communication contexts, driving innovative interference alignment strategies across diverse scenarios.The study in this thesis is divided into multiple segments. The first part establishes the foundation with the problem definition and essential theoretical concepts. The second part delves into the conditions determining the feasibility of interference alignment. These conditions are expressed in terms of the problem dimension and establish the achievable Degree of Freedom (DoF), representing the number of data streams. It explores interference alignment in centralized scenarios, considering both full-rank and reduced-rank Multiple-Input Multiple-Output (MIMO) Interference Broadcast Multiple Access Channel-Interference Channel (IBMAC-IC), addressing real-world complexities. Additionally, it extends the exploration to a distributed scenario, providing a realistic understanding of communication complexities. The third part focuses on optimization techniques, specifically beamforming. It introduces Zero Forcing (ZF) beamforming for both DL and UL User Equipment (UE)s to align CLI in DynTDD systems. It emphasizes the impact of UE-to-UE interference and presents improvements brought by the Weighted Minimum Mean Square Error (WMMSE) algorithms. Furthermore, it explores power allocation optimization using the water-filling algorithm

LTE heterogeneous wireless networks promise significant increase in data rates and improved coverage through (i) the deployment of relays and cell densification, (ii) carrier aggregation to enhance bandwidth usage and (iii) by enabling nodes to have dual connectivity. These emerging cellular networks are complex and large systems which are difficult to optimize with centralized control and where mobiles need to balance spectral efficiency, power consumption and fairness constraints. In this dissertation we focus on how decentralized and autonomous mobiles in multihop cellular systems can optimize their own local objectives by taking into account end-to-end or network-wide conditions. We propose several link-adaptive schemes where nodes can adjust their transmit power, aggregate carriers and select points of access to the network (relays and/or macrocell base stations) autonomously, based on both local and global conditions. Under our approach, this is achieved by disseminating the dynamic congestion level in the backhaul links of the points of access. As nodes adapt locally, the congestion levels in the backhaul links can change, which can in turn induce them to also change their adaptation objectives. We show that under our schemes, even with this dynamic congestion feedback, nodes can distributedly converge to a stable selection of transmit power levels and points of access. We also analytically derive the transmit power levels at the equilibrium points for certain cases. Moreover, through numerical results we show that the corresponding system throughput is significantly higher than when nodes adapt greedily following traditional link layer optimization objectives. Given the growing data rate demand, increasing system complexity and the difficulty of implementing centralized cross-layer optimization frameworks, our work simplifies resource allocation in heterogeneous cellular systems. Our work can be extended to any multihop wireless system where the backhaul link capacity is limited and feedback on the dynamic congestion levels at the access points is available.
Ph. D.

Understanding and characterizing the processes driving social interactions is one of the fundamental problems in social network research. A particular instance of this problem, known as link prediction, has recently attracted considerable attention in various research communities. Link prediction has many important commercial applications, e.g., recommending friends in an online social network such as Facebook and suggesting interesting pins in a collection sharing network such as Pinterest. This work is focused on the temporal link prediction problem: Given a sequence of graph snapshots G1, · ··, Gt from time 1 to t, how do we predict links in future time t + 1? To perform link prediction in a network, one needs to construct models for link probabilities between pairs of nodes. A temporal latent space model is proposed that is built upon latent homophily assumption and temporal smoothness assumption. First, the proposed modeling allows to naturally incorporate the well-known homophily effect (birds of a feather flock together). Namely, each dimension of the latent space characterizes an unobservable homogeneous attribute, and shared attributes tend to create a link in a network.

Les xarxes d'interconnexió tenen com un dels seus objectius principals comunicar i enllaçar els nodes de processament dels sistemes de còmput d'altes prestacions. En aquest context, les fallades de xarxa tenen un impacte considerablement alt, ja que la majoria dels algorismes d'encaminament no van ser dissenyats per tolerar aquestes anomalies. A causa d'això, fins i tot una única fallada d'enllaç té la capacitat d'embussar missatges a la xarxa, provocant situacions de bloqueig o, encara pitjor, és capaç d'impedir la correcta finalització de les aplicacions que es trobin en execució en el sistema de còmput. En aquesta tesi presentem polítiques d'encaminament tolerants a fallades basades en els conceptes d'adaptabilitat i evitació de bloquejos, dissenyades per a xarxes afectades per un gran nombre de fallades d'enllaços. Es presenten dues contribucions al llarg de la tesi, a saber: un mètode d'encaminament tolerant a fallades multicamí, i una tècnica nova i escalable d'evitació de bloquejos. La primera de les contribucions de la tesi és un algorisme d'encaminament adaptatiu multicamí, anomenat Fault-tolerant Distributed Routing Balancing (FT-DRB), que permet explotar la redundància de camins de comunicació de les topologies de xarxa actuals, a fi de proveir tolerància a fallades a les xarxes d'interconnexió. La segona contribució de la tesi és la tècnica escalable d'evitació de bloquejos Non-blocking Adaptive Cycles (NAC). Aquesta tècnica va ser específicament dissenyada per funcionar en xarxes d'interconnexió que presentin un gran nombre de fallades d'enllaços. Aquesta tècnica va ser dissenyada i implementada amb la finalitat de servir al mètode d'encaminament descrit anteriorment, FT-DRB.
Las redes de interconexión tienen como uno de sus objetivos principales comunicar y enlazar los nodos de procesamiento de los sistemas de cómputo de altas prestaciones. En este contexto, los fallos de red tienen un impacto considerablemente alto, ya que la mayoría de los algoritmos de encaminamiento no fueron diseñados para tolerar dichas anomalías. Debido a esto, incluso un único fallo de en un enlace tiene la capacidad de atascar mensajes en la red, provocando situaciones de bloqueo o, peor aún, es capaz de impedir la correcta finalización de las aplicaciones que se encuentren en ejecución en el sistema de cómputo. En esta tesis presentamos políticas de encaminamiento tolerantes a fallos basadas en los conceptos de adaptabilidad y evitación de bloqueos, diseñadas para redes de comunicación afectadas por un gran número de fallos de enlaces. Se presentan dos contribuciones a lo largo de la tesis, a saber: un método de encaminamiento tolerante a fallos multicamino, y una novedosa y escalable técnica de evitación de bloqueos. La primera de las contribuciones de la tesis es un algoritmo de encaminamiento adaptativo multicamino, denominado Fault-tolerant Distributed Routing Balancing (FT-DRB), que permite explotar la redundancia de caminos de comunicación de las topologías de red actuales, a fin de proveer tolerancia a fallos a las redes de interconexión. La segunda contribución de la tesis es la técnica escalable de evitación de bloqueos Non-blocking Adaptive Cycles (NAC). Dicha técnica fue específicamente diseñada para funcionar en redes de interconexión que presenten un gran número de fallos de enlaces. Esta técnica fue diseñada e implementada con la finalidad de servir al método de encaminamiento descrito anteriormente, FT-DRB.
Interconnection networks communicate and link together the processing units of modern high-performance computing systems. In this context, network faults have an extremely high impact since most routing algorithms have not been designed to tolerate faults. Because of this, as few as one single link failure may stall messages in the network, leading to deadlock configurations or, even worse, prevent the finalization of applications running on computing systems. In this thesis we present fault-tolerant routing policies based on concepts of adaptability and deadlock freedom, capable of serving interconnection networks affected by a large number of link failures. Two contributions are presented throughout this thesis, namely: a multipath fault-tolerant routing method, and a novel and scalable deadlock avoidance technique. The first contribution of this thesis is the adaptive multipath routing method Fault-tolerant Distributed Routing Balancing (FT-DRB). This method has been designed to exploit the communication path redundancy available in many network topologies, allowing interconnection networks to perform in the presence of a large number of faults. The second contribution is the scalable deadlock avoidance technique Non-blocking Adaptive Cycles (NAC), specifically designed for interconnection networks suffering from a large number of failures. This technique has been designed and implemented with the aim of ensuring freedom from deadlocks in the proposed fault-tolerant routing method FT-DRB.

The remarkable evolution of wireless networks into the next generation to provide ubiquitous and seamless broadband applications has recently triggered the emergence of Wireless Mesh Networks (WMNs). The WMNs comprise stationary Wireless Mesh Routers (WMRs) forming Wireless Backbone Mesh Networks (WBMNs) and mobile Wireless Mesh Clients (WMCs) forming the WMN access. While WMCs are limited in function and radio resources, the WMRs are expected to support heavy duty applications : that is, WMRs have gateway and bridge functions to integrate WMNs with other networks such as the Internet, cellular, IEEE 802.11, IEEE 802.15, IEEE 802.16, sensor networks, et cetera. Consequently, WMRs are constructed from fast switching radios or multiple radio devices operating on multiple frequency channels. WMRs are expected to be self-organized, self-configured and constitute a reliable and robust WBMN which needs to sustain high traffic volumes and long "online" time. However, meeting such stringent service expectations requires the development of decentralized dynamic transmission power control (DTPC) approaches. This thesis addresses the DTPC problem for both single and multiple channel WBMNs. For single channel networks, the problem is formulated as the minimization of both the link-centric and network-centric convex cost function. In order to solve this issue, multiple access transmission aware (MATA) models and algorithms are proposed. For multi-radio multi-channel (MRMC) WBMNs, the network is modelled as sets of unified channel graphs (UCGs), each consisting of interconnected active network users communicating on the same frequency channel. For each UCG set, the minimization of stochastic quadratic cost functions are developed subject to the dynamic Link State Information (LSI) equations from all UCGs. An energy-efficient multi-radio unification protocol (PMMUP) is then suggested at the Link-Layer (LL). Predictive estimation algorithms based on this protocol are proposed to solve such objective functions. To address transmission energy and packet instabilities, and interference across multiple channels, singularly-perturbed weakly-coupled (SPWC) control problems are formulated. In order to solve the SPWC transmission power control problem, a generalized higher-order recursive algorithm (HORA) that obtains the Riccati Stabilizing Solutions to the control problem is developed. The performance behaviours of the proposed models and algorithms are evaluated both analytically and through computer simulations. Several simulations are performed on a large number of randomly generated topologies. Simulation and analytical results confirm the efficacy of the proposed algorithms compared to the most recently studied techniques

There is an ever increasing demand of electricity and to meet this demand, installation of new transmission and distribution lines is required. This task requires a significant investment and consent from the respective authorities. An alternative is to utilize maximum capability of the existing lines. Static line ratings are based on a conservative estimate, which means that on most occasions, the actual capacity of lines is much higher than the static line ratings. In order to provide a solution to this problem, this thesis introduces an approach that has been developed to utilize real time weather conditions, conductor sag data and the actual line loading of the conductor from PMU to provide dynamic line ratings for active distribution networks. The application has been developed in LabVIEW environment which provides a user friendly front panel where real-time ampacity can be seen as a waveform while being compared to the actual line loading.  The developed application has been tested on the reference grid created for IDE4L project. The ampacity calculation method introduced here makes use of real-time data available through a real-time simulator in SmarTS lab at KTH, Sweden.
Det är ett ökande behov av elektricitet och för att möta detta behövet, installation av nya transmission och distributionsledningar behövs. Denna utbyggnad kräver ett stort engagemang och förståelse från ansvariga grupper. Ett alternativ är att utnyttja max-kapaciteten på redan befintliga ledningar. Installerade ledningar har räknats på ett konservativt sätt, vilket innebär att det vid vissa tillfällen går att öka belastingen på på dessa. För att ge en lösning på detta problem, introducerar den här avhandlingen en metod för att använda realtids-väderdata, tabeller för ledningarnas utvidgning och realtids-belastningsdata från PMU för att framställa dynamisk data för aktiva distributions-nätverk. Applikationen har utvecklas i LabVIEW-miljön som har ett användarvänligt GUI, där “Real-time ampacity” kan ses som en vågform medans den jämförs mot den faktiska belastningen på ledningen.  Den utvecklade appliktionen har testats på referens-miljön som skapts för IDE4L projektet. “Ampacity calculation metoden” som introduceras här använder sig av realtidsdata som görs tillgänglig igenom en realtids-simulator i SmarTSlab på Kungliga Tekniska Högskolan i Sverige.

Vast application of ITS and the availability of numerous on-road detection devices has resulted in variety of alternative data sources to be exploited and used in the field of traffic modelling. In this thesis, historical travel times, as an alternative data source, is employed on the developed method to perform dynamic network loading. The developed method, referred to as DNLTT, uses the share of each route available in the route choice set from the initial demand, as well as link travel times to perform the network loading. The output of the algorithm is time-dependent link flows. DNLTT is applied on Stockholm transportation network, where it is expected to have variation in link travel times in different time-periods, due to network congestion. In order to calculate the route shares, a time-sliced OD matrix is used. The historical travel times and the routes in the route choice set are extracted from an existing route planning tool. An available logit model, which considers the route travel time as the only logit parameter, is used for the route share calculation and the network loading is performed according to 2 different methods of DNLTT and DL. The evaluation of results is done for a toy network, where there happen different network states in different time-periods. Furthermore, the model output from Stockholm case study is analyzed and evaluated. The dynamic behavior of DNLTT is studied by analysis of link flows in different time-periods. Furthermore, the resulting link flows from both network loading methods are compared against observed link flows from radar sensors and the statistical analysis of link flows is performed accordingly. DNLTT exhibits a better performance on the toy network compared to DL, where the increasing link travel times cause the link flows to decline in different time-periods. However, the output of the developed method does not resemble the observed link flows for the investigated links in Stockholm case study. It is strongly believed, that the performance of DNLTT on the investigated transportation network potentially improves, in case the historical travel times better resemble the network dynamics. In addition to a more reliable data set, an OD adjustment process in all the time-periods is believed to generate better model output.

Over the last several decades, electricity consumption and generation have continually grown. Investment in the Transmission and Distribution (T&D) infrastructure has been minimal and it has become increasingly difficult and expensive to permit and build new power lines. At the same time, a growing increase in the penetration of renewable energy resources is causing an unprecedented level of dynamics on the grid. Consequently, the power grid is congested and under stress. To compound the situation, the utilities do not possess detailed information on the status and operating margins on their assets in order to use them optimally. The task of monitoring asset status and optimizing asset utilization for the electric power industry seems particularly challenging, given millions of assets and hundreds of thousands of miles of power lines distributed geographically over millions of square miles. The lack of situational awareness compromises system reliability, and raises the possibility of power outages and even cascading blackouts. To address this problem, a conceptual Power Line Sensor Network (PLSN) is proposed in this research. The main objective of this research is to develop a distributed PLSN to provide continuous on-line monitoring of the geographically dispersed power grid by using hundreds of thousands of low-cost, autonomous, smart, and communication-enabled Power Line Sensor (PLS) modules thus to improve the utilization and reliability of the existing power system. The proposed PLSN specifically targets the use of passive sensing techniques, focusing on monitoring the real-time dynamic capacity of a specific span of a power line under present weather conditions by using computational intelligence technologies. An ancillary function is to detect the presence of incipient failures along overhead power lines via monitoring and characterizing the electromagnetic fields around overhead conductors. This research integrates detailed modeling of the power lines and the physical manifestations of the parameters being sensed, with pattern recognition technologies. Key issues of this research also include design of a prototype PLS module with integrated sensing, power and communication functions, and validation of the Wireless Sensor Network (WSN) technology integrated to this proposed PLSN.

2008 - 2009
Based on a qualitative research approach, this paper explores how four highly successful biotechnology organizations source their most critical input-scientific knowledge and integrate it inside. We selected matched pairs of organizations that operated under similar conditions and regulatory regimes (Southern Italy) but differed considerably with regard to ownership (public and private). We find that scientists enter into large numbers of collaborative research efforts (frequently informal) with scientists at other organizations, especially universities. Formal market contracts are also used to govern these exchanges of scientific knowledge. Inside, the main job in integrating new information and knowledge, is carried up by few critical connectors. Our findings suggest that the reputation is the real, effective intangible resource at the base of these relational activities for value creation in all the cases. We selected the Dynamic Capabilities (DCs) model proposed by Teece, Pisano, Shuen, 1997 and by Teece, 2007, as the core theoretical guideline for the present study. Following DCs, we consider the places where basic and applied research meet as the “critical-zone” for value creation in biotech organizations. Another analytical tool is the network approach to find and fix the critical organizational dimensions under network domains. Our findings enable a future research pattern based on a tested informal relation codification. It will be possible to implement a quantitative research on a higher number of observations. This thesis is divided into the following sections. In chapter I, the research topic is presented as an empirical, real-changing movement, drawing on the case of USA and its national biotech-innovation system, in other words the change in the relational dynamic between basic and applied research. As such, the formulation of the general research question emerges out of a simple consideration of the corresponding problem for the Italian context, specifically southern Italy. Chapter II deals with the method and research questions and describes the modes of organizing the analysis. As the method is qualitative and focused on case studies, this section also presents the theoretical issues we referred to for data analysis and evidence discussion. We refer, here, to the dynamic capabilities theoretical approach presented mainly in two fundamental articles by Teece et al. on 1997 and by Teece on 2007. Additional theoretical subjects are outlined in chapter III. These arguments complement the research context by providing a bird's-eye view at organization analysis and social network contributions. Our attempt is to find some insights into where strategy scholars might look for hidden resource for value. Here the fundamental contributions are those of Jones, Hesterly, Borgatti (1997), of Cross, Borgatti, Parker (2002), Cross, Parker (2004), and of Powell and Grodal (2006). The section, finally, presents the empirical analysis, starting from firms’ description, data collection and data analysis. In this section we focus more on explaining the construction of the SNA questions and the measures of DCs. In Chapter IV the findings are grouped in three key-issues: configuration of Biotech Firms’ relational and integrative capabilities and value implications, evidence in terms of process-position-path and (organizational) convergence solutions, basic vs applied research networks: governance and incentive issues. In a final section, we collected the ending notes and the future research agenda. [edited by author]
VIII n.s.

Companies, across the globe are concerned with risks that impair their ability to produce quality products at a low cost and deliver them to customers on time. Risk assessment, comprising of both external and internal elements, prepares companies to identify and manage the risks affecting them. Although both external/supply chain and internal/production line risk assessments are necessary, internal risk assessment is often ignored. Internal risk assessment helps companies recognize vulnerable sections of production operations and provide opportunities for risk mitigation. In this research, a novel production line risk assessment methodology is proposed. Traditional simulation techniques fail to capture the complex relationship amongst risk events and the dynamic interaction between risks affecting a production line. Bayesian- integrated System Dynamics modelling can help resolve this limitation. Bayesian Belief Networks (BBN) effectively capture risk relationships and their likelihoods. Integrating BBN with System Dynamics (SD) for modelling production lines help capture the impact of risk events on a production line as well as the dynamic interaction between those risks and production line variables. The proposed methodology is applied to an industrial case study for validation and to discern research and practical implications.

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Energias Renováveis – Conversão Eléctrica e Utilização Sustentáveis
One of the current challenges the electricity grid has is to actively connect future generation to its network without the need to fully reinforce it. This dissertation will study the use of dynamic ratings on overhead lines to increase its capacity and thus defer major investment on infrastructure reinforcement. The amount of current an overhead line can withstand in a given time is defined by the distance towards the ground, which is proportional to the conductor´s temperature, which is given by a static rating stated in the P27 standard – “Current Rating Guide for High Voltage Overhead Lines Operating in the UK Distribution System”. This rating changes from season to season and depends on specific values for ambient temperature, wind speed, wind direction and the probability that in a year the conductor exceeds its design temperature. This standard is seen as being very restrictive and a limiting factor on overhead line capacity for both future generation connections and demand. Wind speed and direction are extremely important on the cooling of overhead lines and in times of strong winds the conductor cools down, allowing extra amount of current to flow through it. By using real time weather data, it´s possible to obtain the maximum current that can flow in an overhead line for a specific operating temperature and assess the amount of headroom possible given by the difference between the static ratings and the new dynamic ratings is assessed. A view on the extra amount of energy produced, as well as CO2 emission savings and profit will also be presented, giving a practical result by applying dynamic ratings.

Un flot de liens est un ensemble de liens {(t,u,v)} dans lequel un triplet (t,u,v) modélise l'interaction entre deux entités u et v à l'instant t. Dans de nombreuses situations, les données résultent de la mesure des interactions entre plusieurs millions d'entités au cours du temps et peuvent ainsi être étudiées grâce au formalisme des flots de liens. C'est le cas des appels téléphoniques, des échanges d'e-mails, des transferts d'argent, des contacts entre individus, du trafic IP, des achats en ligne, et bien d'autres encore. L'objectif de cette thèse est la détection d'ensembles de liens anormaux dans un flot de liens. Dans une première partie, nous concevons une méthode qui construit différents contextes, un contexte étant un ensemble de caractéristiques décrivant les circonstances d'une anomalie. Ces contextes nous permettent de trouver des comportements inattendus pertinents, selon plusieurs dimensions et perspectives. Dans une seconde partie, nous concevons une méthode permettant de détecter des anomalies dans des distributions hétérogènes dont le comportement est constant au cours du temps, en comparant une séquence de distributions hétérogènes similaires. Nous appliquons nos outils méthodologiques à des interactions temporelles provenant de retweets sur Twitter et de trafic IP du groupe MAWI
A link stream is a set of links {(t, u, v)} in which a triplet (t, u, v) models the interaction between two entities u and v at time t. In many situations, data result from the measurement of interactions between several million of entities over time and can thus be studied through the link stream's formalism. This is the case, for instance, of phone calls, email exchanges, money transfers, contacts between individuals, IP traffic, online shopping, and many more. The goal of this thesis is the detection of sets of abnormal links in a link stream. In a first part, we design a method that constructs different contexts, a context being a set of characteristics describing the circumstances of an anomaly. These contexts allow us to find unexpected behaviors that are relevant, according to several dimensions and perspectives. In a second part, we design a method to detect anomalies in heterogeneous distributions whose behavior is constant over time, by comparing a sequence of similar heterogeneous distributions. We apply our methodological tools to temporal interactions coming from retweets of Twitter and IP traffic of MAWI group

Le dinamiche, la struttura e la funzione sono intimamente legate nei sistemi proteici (Karplus et al. 2005, Philos. Trans. A Math. Phys. Eng. Sci., Bahar et al. 2010 Annu. Rev. Biophys.) e la caratterizzazione a livello atomico delle dinamiche delle proteine è essenziale per comprendere i loro aspetti funzionali. Lo studio della relazione dinamica-struttura-funzione nelle proteine può anche avere un impatto ben oltre la ricerca di base per lo sviluppo di applicazioni biotecnologiche e farmacologiche (Ozbabacan et al. 2010 Curr. Opin. Drug Discov. Devel.). In questo progetto di dottorato, abbiamo impiegato simulazioni di Dinamica Molecolare (MD) in solvente esplicito per studiare le dinamiche di diverse proteine bersaglio associate allo sviluppo di malattie umane. Le simulazioni MD hanno il potenziale per descrivere efficacemente i moti proteici che avvengono su diverse scale temporali e per caratterizzare ensemble strutturali a livello atomico, specialmente se integrate da tecniche di campionamento più accurate o da dati sperimentali (Dror et al. 2012 Annu. Rev. Biophys., Sutto et al. 2012 Wiley Interdiscip. Rev. Comput. Mol. Sci.). In particolare abbiamo integrato le nostre simulazioni con dati biofisici sperimentali in maniera da superare le limitazioni intrinseche nelle simulazioni MD associate all’accuratezza dei forcefield (il modello fisico utilizzato per descrivere la proteina e l'ambiente) e al campionamento conformazionale. Nell'analisi delle simulazioni MD sono stati utilizzati anche metodi ispirati alla teoria dei grafi per descrivere la comunicazione strutturale che occorre tra siti distali della proteina durante la dinamica (Papaleo et al. 2012 PLoS One, Ghosh et al. 2007 Proc. Natl. Acad. Sci. USA). In particolare, nei nostri studi ci siamo concentrati su proteine che appartengono alla classe delle proteine intrinsecamente disordinate (IDP) e fattori di trascrizione, che sono entrambi frequentemente associate con lo sviluppo di cancro o malattie neurodegenerative. Come esempi di IDP abbiamo scelto il dominio C-terminale di Sic1 (Brocca et al. 2011, Biophys. J.) e le regioni disordinate dell’Atassina-3 umana (Saunders et al., 2009 Protein Ing. Des. Sel.) per fornire una descrizione della loro eterogeneità strutturale in soluzione e identificare le variazioni conformazionali associate all’interazione con partner biologici (Lambrughi et al. 2012 Front. Physiol.; Invernizzi et al. 2013 BBA Gen. Subj.). Per raggiungere questo obiettivo, abbiamo integrato simulazioni MD con spettroscopie biofisiche, come la spettroscopia NMR grazie ad un periodo di ricerca presso lo Structural Biology and NMR Laboratory presso l'Università di Copenhagen (DK) nel gruppo del Prof. Kaare Teilum, sotto la supervisione del Dr. Gaetano Invernizzi. Come esempi di fattori di trascrizioni ci siamo concentrati sull’oncosoppressore p53 e su domini zinc-finger per studiare gli effetti indotti dall’interazione con il DNA e le alterazioni strutturali associate alla sostituzione dello zinco con altri ioni metallici non essenziali come il cadmio: un metallo tossico e noto agente cancerogeno nell'uomo (IARC Monogr. Eval. Carcinog. Risks. Hum. 1993). Poiché nei forcefield attualmente esistenti non sono disponibili parametri sufficientemente precisi per descrivere efficacemente la coordinazione con ioni metallici nelle proteine, abbiamo sviluppato un protocollo basato sulla meccanica molecolare classica e calcoli chimici quantistici per derivare nuovi parametri ottimizzati per lo zinco e il cadmio, che possono poi essere utilizzati in simulazioni MD.
Protein dynamics, structure and function are intimately linked in many protein systems (Karplus et al. 2005, Philos. Trans. A Math. Phys. Eng. Sci., Bahar et al. 2010 Annu. Rev. Biophys.). Thus, the characterization of the protein dynamics in atomistic details can be important to understand functional aspects of these fundamental cellular components. The study of dynamics-structure-function relationship in proteins may also have impact well-beyond fundamental research for biotechnological or pharmacological applications (Ozbabacan et al. 2010 Curr. Opin. Drug Discov. Devel.). In this Ph.D. project, we employed all-atom and explicit solvent Molecular Dynamics (MD) simulations to study protein dynamics of several target proteins that are related to human diseases. MD simulations have the potential to describe motions occurring on different timescales and to characterize protein structural ensembles at the atom-level if integrated to more accurate sampling techniques or to experimental data (Dror et al. 2012 Annu. Rev. Biophys., Sutto et al. 2012 Wiley Interdiscip. Rev. Comput. Mol. Sci.). Indeed, we here integrated our simulations with experimental biophysical data to overcome intrinsic limitations in MD simulations due to force field accuracy (the physical model used to describe the protein and the environment in our simulations) and conformational sampling. The analysis of our MD simulations have been also accompanied by methods inspired by graph theory to describe structural communication occurring between distal sites in the protein during dynamics (Papaleo et al. 2012 PLoS One, Ghosh et al. 2007 Proc. Natl. Acad. Sci. USA). In particular, we focused in our studies on target proteins that belong to the class of intrinsically disordered proteins (IDPs) and transcription factors, which are both often associated with cancer or neurodegenerative diseases. As examples of IDPs we selected the C-terminal domain of yeast Sic1 (Brocca et al. 2011, Biophys. J.) and the disordered regions of human Ataxin-3 (Saunders et al. 2009 Protein Eng. Des. Sel.) to provide a description of their heterogeneous ensemble in solution and to identify structures that resemble the conformations bound to their biological partners (Lambrughi et al. 2012 Front. Physiol.; Invernizzi et al. 2013 BBA Gen. Subj.). To achieve this goal, we integrated MD simulations with biophysical spectroscopies, and especially NMR thanks to a visiting period at the Structural Biology and NMR Laboratory at the University of Copenhagen (Dk) in the group of Prof. Kaare Teilum, under the supervision of Dr. Gaetano Invernizzi. As an example of transcription factor, we focused on p53 and zinc-finger domains to study the effects induced upon DNA-binding and the structural alterations associated with the replacement of zinc with other non-essential metal ions, as cadmium a known toxic metal and human carcinogen (IARC Monogr. Eval. Carcinog. Risks. Hum. 1993). Since no sufficiently accurate parameters are available to describe metal ions in classical MD force field, we have also developed a protocol based on classical molecular mechanics and quantum chemical calculations to derive optimized parameters for zinc and cadmium, which can then be used in MD simulations.

On-board gimbal systems for camera stabilization in helicopters are typically based on linear models. Such models, however, are inaccurate due to system nonlinearities and complexities. As an alternative approach, artificial neural networks can provide a more accurate model of the gimbal system based on their non-linear mapping and generalization capabilities. This thesis investigates the applications of artificial neural networks to model the inertial characteristics (on the azimuth axis) of the inner gimbal in a gyro-stabilized multi-gimbal system. The neural network is trained with time-domain data obtained from gyro rate sensors of an actual camera system. The network performance is evaluated and compared with measured data and a traditional linear model. Computer simulation results show the neural network model fits well with the measured data and significantly outperforms a traditional model.

A identificação dos segmentos críticos da rede viária é um conhecimento básico que todo planejador de transportes deve ter sobre a rede viária. É inevitável a ocorrência de incidentes e eventos de redução da capacidade nos elementos da rede. O efeito de acidentes e obstruções em segmentos críticos da rede ocasionam impactos que prejudicam o desempenho da rede. Este estudo foi desenvolvido com o apoio do modelo de alocação de tráfego do software VISUM (versão 2015) e propõe um método para determinar a importância de cada segmento da rede viária, a identificação de segmentos críticos da rede e a avaliação de sua obstrução de forma estática e dinâmica. Para isso, são utilizados diversos indicadores de desempenho da rede viária. O método foi aplicado na região do Litoral Norte do Rio Grande do Sul, utilizando os dados de tráfego fornecidos pela CONCEPA TRIUNFO, DAER e DNIT. A determinação da importância de cada segmento decorreu da avaliação do impacto na rede causado pela obstrução do próprio segmento. Através do método proposto neste estudo foi possível identificar o segmento crítico da rede viária estudada e, de forma qualitativa, verificar a extensão da obstrução desse segmento nas análises estática e dinâmica Verificou-se que o indicador diferença do total de tempo despendido na rede é o indicador que mais apresenta crescimento com o incremento da demanda, não apresenta alterações de priorização dos segmentos frente a variações de intensidade e sentido da demanda. Os resultados deste estudo mostraram que o segmento crítico da rede pertence a BR-101 entre os municípios de Osório e Terra de Areia. O método de hierarquização proposto independe do sentido e da intensidade da demanda, e está sujeito a mais de uma métrica para avaliar o segmento crítico. Estes resultados podem subsidiar o planejamento de transportes, identificando trechos críticos da rede viária que necessitam de mais atenção dos gestores e apontando medidas de operação no caso de eventos disruptivos nos trechos críticos.
Identifying the most important link of the network is essential knowledge that the transport planners should have over the network. Incidents and events of capacity reduction in network elements are inevitable. The effect of accidents and obstructions on critical network links causes impacts that hamper network performance. This study was developed with support of VISUM (version 2015) traffic assignment model software with proposes a method to determinate each network link importance level, to identify the critical link and to measure the critical link blockage impact on network. For this, several road network performance indicators are used. The method was applied in the North Coast region of Rio Grande do Sul, using traffic data provided by CONCEPA TRIUNFO, DAER and DNIT. The link level importance in define from the own link impact due its obstruction. The proposed method identified the most critical link of the studied network and verified the qualitative impact of its obstruction extent in the static and dynamic assignment analyses It was verified that the measure total spent time difference in the network is the most sensible measure that growth with a demand increase, this measure does not present changes the link importance rank against variations of intensity and direction of demand flow changes. The results of this study show that the critical link of the network belongs to the BR-101 highway between the municipalities of Osório and Terra de Areia. The proposed hierarchical method developed with several metrics measures fond the critical link in an independent demand direction and intensity analysis. The findings may support transport planners to identify the most critical arc of a network. To better implement resources of road management and repairs. Also identify where the operation measures may be implanted in face a disruptive event on a critical link.

Abstract Critical Infrastructures (CIs) are an integral part of our society and economy. Services like electricity supply or telecommunication services are expected to be available at all times and a service failure may have catastrophic consequences for society or economy. Current CI protection strategies are from a time when CIs or CI sectors could be operated more or less self-sufficient and interconnections among CIs or CI sectors, which may lead to cascading service failures to other CIs or CI sectors, where not as omnipresent as today. In this PhD thesis, a cross-sector CI model for on-line risk monitoring of CI services, called CI security model, is presented. The model allows to monitor a CI service risk and to notify services that depend on it of possible risks in order to reduce and mitigate possible cascading failures. The model estimates CI service risk by observing the CI service state as measured by base measurements (e.g. sensor or software states) within the CI service components and by observing the experienced service risk of CI services it depends on (CI service dependencies). CI service risk is estimated in a probabilistic way using a Bayesian network based approach. Furthermore, the model allows CI service risk prediction in the short-term, mid-term and long-term future, given a current CI service risk and it allows to model interdependencies (a CI service risk that loops back to the originating service via dependencies), a special case that is difficult to model using Bayesian networks. The representation of a CI as a CI security model requires analysis. In this PhD thesis, a CI analysis method based on the PROTOS-MATINE dependency analysis methodology is presented in order to analyse CIs and represent them as CI services, CI service dependencies and base measurements. Additional research presented in this PhD thesis is related to a study of assurance indicators able to perform an on-line evaluation of the correctness of risk estimates within a CI service, as well as for risk estimates received from dependencies. A tool that supports all steps of establishing a CI security model was implemented during this PhD research. The research on the CI security model and the assurance indicators was validated based on a case study and the initial results suggest its applicability to CI environments
Tiivistelmä Tässä väitöskirjassa esitellään läpileikkausmalli kriittisten infrastruktuurien jatkuvaan käytön riskimallinnukseen. Tämän mallin avulla voidaan tiedottaa toisistaan riippuvaisia palveluita mahdollisista vaaroista, ja siten pysäyttää tai hidastaa toisiinsa vaikuttavat ja kumuloituvat vikaantumiset. Malli analysoi kriittisen infrastruktuurin palveluriskiä tutkimalla kriittisen infrastruktuuripalvelun tilan, joka on mitattu perusmittauksella (esimerkiksi anturi- tai ohjelmistotiloina) kriittisen infrastruktuurin palvelukomponenttien välillä ja tarkkailemalla koetun kriittisen infrastruktuurin palveluriskiä, joista palvelut riippuvat (kriittisen infrastruktuurin palveluriippuvuudet). Kriittisen infrastruktuurin palveluriski arvioidaan todennäköisyyden avulla käyttämällä Bayes-verkkoja. Lisäksi malli mahdollistaa tulevien riskien ennustamisen lyhyellä, keskipitkällä ja pitkällä aikavälillä, ja mahdollistaa niiden keskinäisten riippuvuuksien mallintamisen, joka on yleensä vaikea esittää Bayes-verkoissa. Kriittisen infrastruktuurin esittäminen kriittisen infrastruktuurin tietoturvamallina edellyttää analyysiä. Tässä väitöskirjassa esitellään kriittisen infrastruktuurin analyysimenetelmä, joka perustuu PROTOS-MATINE -riippuvuusanalyysimetodologiaan. Kriittiset infrastruktuurit esitetään kriittisen infrastruktuurin palveluina, palvelujen keskinäisinä riippuvuuksina ja perusmittauksina. Lisäksi tutkitaan varmuusindikaattoreita, joilla voidaan tutkia suoraan toiminnassa olevan kriittisen infrastruktuuripalvelun riskianalyysin oikeellisuutta, kuin myös riskiarvioita riippuvuuksista. Tutkimuksessa laadittiin työkalu, joka tukee kriittisen infrastruktuurin tietoturvamallin toteuttamisen kaikkia vaiheita. Kriittisen infrastruktuurin tietoturvamalli ja varmuusindikaattorien oikeellisuus vahvistettiin konseptitutkimuksella, ja alustavat tulokset osoittavat menetelmän toimivuuden
Kurzfassung In dieser Doktorarbeit wird ein Sektorübergreifendes Modell für die kontinuierliche Risikoabschätzung von kritische Infrastrukturen im laufenden Betrieb vorgestellt. Das Modell erlaubt es, Dienstleistungen, die in Abhängigkeit einer anderen Dienstleistung stehen, über mögliche Gefahren zu informieren und damit die Gefahr des Übergriffs von Risiken in andere Teile zu stoppen oder zu minimieren. Mit dem Modell können Gefahren in einer Dienstleistung anhand der Überwachung von kontinuierlichen Messungen (zum Beispiel Sensoren oder Softwarestatus) sowie der Überwachung von Gefahren in Dienstleistungen, die eine Abhängigkeit darstellen, analysiert werden. Die Abschätzung von Gefahren erfolgt probabilistisch mittels eines Bayessches Netzwerks. Zusätzlich erlaubt dieses Modell die Voraussage von zukünftigen Risiken in der kurzfristigen, mittelfristigen und langfristigen Zukunft und es erlaubt die Modellierung von gegenseitigen Abhängigkeiten, die im Allgemeinen schwer mit Bayesschen Netzwerken darzustellen sind. Um eine kritische Infrastruktur als ein solches Modell darzustellen, muss eine Analyse der kritischen Infrastruktur durchgeführt werden. In dieser Doktorarbeit wird diese Analyse durch die PROTOS-MATINE Methode zur Analyse von Abhängigkeiten unterstützt. Zusätzlich zu dem vorgestellten Modell wird in dieser Doktorarbeit eine Studie über Indikatoren, die das Vertrauen in die Genauigkeit einer Risikoabschätzung evaluieren können, vorgestellt. Die Studie beschäftigt sich sowohl mit der Evaluierung von Risikoabschätzungen innerhalb von Dienstleistungen als auch mit der Evaluierung von Risikoabschätzungen, die von Dienstleistungen erhalten wurden, die eine Abhängigkeiten darstellen. Eine Software, die alle Aspekte der Erstellung des vorgestellten Modells unterstützt, wurde entwickelt. Sowohl das präsentierte Modell zur Abschätzung von Risiken in kritischen Infrastrukturen als auch die Indikatoren zur Uberprüfung der Risikoabschätzungen wurden anhand einer Machbarkeitsstudie validiert. Erste Ergebnisse suggerieren die Anwendbarkeit dieser Konzepte auf kritische Infrastrukturen

L’objet de cette thèse porte sur le concept de réseau complexe associé à de l’information textuelle. Nous nous sommes intéressés à l’analyse de ces réseaux avec une perspective d’application aux réseaux sociaux. Notre première contribution a consisté à réaliser un modèle d’analyse pour un réseau social dynamique en utilisant l’approche de modélisation à base d’agents (agent based modeling ou ABM), modèle auteur-sujet du text-mining (« author-topic modeling » ou ATM), et en ayant recours à le cadre mathématique de la prétopologie pour représenter la proximité des sujets. Notre modélisation se nomme Textual-ABM. Notre démarche a été d’utiliser le modèle auteur-sujet pour estimer l’intérêt de l’utilisateur sur la base du contenu textuel et d’employer la prétopologie pour modéliser plusieurs relations et représenter un ensemble de voisinages plus élaboré qu’une simple relation. Notre deuxième contribution concerne la diffusion des informations sur un réseau social « hétérogène ». Nous proposons d’étendre le modèle de diffusion épidémique independant cascade model (IC) et le modèle de diffusion en cascade prétopologique que nous nommons respectivement Textual-Homo-IC et Textual-PCM. Pour Textual-Homo-IC, la probabilité d’infection est basée sur l’homophilie c’est-à-dire l’affiliation à des agents ressemblants, celle-ci est obtenue à partir du contenu textuel en utilisant le modèle de sujet (topic modeling). Pour Textual-PCM, une fonction d’adhérence (pseudo-closure function) avec différentes variantes d’association pour les relations qui la constitue est proposée pour réaliser un ensemble de voisinages plus complexe. En outre, nous proposons d’utiliser l’apprentissage supervisé pour prédire la diffusion d’un sujet avec une combinaison de facteurs intrinsèques ou externes. Notre troisième contribution concerne la présiction des relations entre co-auteurs avec l’ajout d’une nouvelle caractéristique topologique liés aux facteurs géographiques et fonctionnalités de contenu à l’aide du topic modeling. L’ensemble de ces travaux est accompagné d’une partie expérimentale et de la présentation des algorithmes développés
This thesis deals with the concept of complex network associated with textual information. We are interested in the analysis of these networks with a perspective of application to social networks. Our first contribution consisted in building an analysis model for a dynamic social network using the agent based modeling (ABM) approach, author-topic modeling (ATM), and using the mathematical framework of pretopology to represent the proximity of the subjects. Our modeling is called Textual-ABM. Our proposal has been to use author-topic modeling to estimate user interest based on text content and to use pretopology to model several relationships and to represent a set of neighborhoods that is more elaborate than a simple relationship. Our second contribution concerns the diffusion of information on a "heterogeneous" social network. We propose to extend the independent cascade epidemic diffusion model (IC) and the pretopological cascade diffusion model that we call Textual-Homo-IC and Textual-PCM respectively. For Textual-Homo-IC, the probability of infection is based on homophilia (resemblance of agents) which is obtained from the textual content using the topic modeling. For Textual-PCM, a pseudo-closure function with different strong levels is proposed to realize a more complex set of neighborhoods. In addition, we propose to use supervised learning to predict the diffusion of a topic with a combination of intrinsic or external factors. Our third contribution concerns the prediction of relationships between co-authors with the addition of a new topological feature related to geographical factors and content features using topic modelling. All this work was achieved by the design of specific algorithms and validated by experiments

Batch reactor is an essential unit operation in almost all batch-processing industries. Different types of reaction schemes (such as series, parallel and complex) and different order of model complexity (short-cut, detailed, etc. ) result in different sets of model equations and computer coding of all possible sets of model equations is cumbersome and time consuming. In this work, therefore, a general computer program (GBRM - General Batch Reactor Model) is developed to generate all possible sets of equations automatically and as required. GBRM is tested for different types of reaction schemes and for different order of model complexity and its flexibility is demonstrated. The above GBRM computer program is lodged with Dr. I. M. Mujtaba. One of the challenges in batch reactors is to ensure desired performance of individual batch reactor operations. Depending on the requirement and the objective of the process, optimisation in batch reactors leads to different types of optimisation problems such as maximum conversion, minimum time and maximum profit problem. The reactor temperature, jacket temperature and jacket flow rate are the main control variables governing the process and these are optimised to ensure maximum benefit. In this work, an extensive study on mainly conventional batch reactor optimisation is carried out using GBRM coupled with efficient DAEs (Differential and Algebraic Equations) solver, CVP (Control Vector Parameterisation) technique and SQP (Successive Quadratic Programming) based optimisation technique. The safety, environment and product quality issues are embedded in the optimisation problem formulations in terms of constraints. A new approach for solving optimisation problem with safety constraint is introduced. All types of optimisation problems mentioned above are solved off-line, which results to optimal operating policies. The off-line optimal operating policies obtained above are then implemented as set points to be tracked on-line and various types of advanced controllers are designed for this purpose. Both constant and dynamic set points tracking are considered in designing the controllers. Here, neural networks are used in designing Direct Inverse and Inverse-Model-Based Control (IMBC) strategies. In addition, the Generic Model Control (GMC) coupled with on-line neural network heat release estimator (GMC-NN) is also designed to track the optimal set points. For comparison purpose, conventional Dual Mode (DM) strategy with PI and PID controllers is also designed. Robustness tests for all types of controllers are carried out to find the best controller. The results demonstrate the robustness of GMC-NN controller and promise neural controllers as potential robust controllers for future. Finally, an integrated framework (BATCH REACT) for modelling, simulation, optimisation and control of batch reactors is proposed.

Frequency monitoring network (FNET) is an Internet based GPS synchronized wide-area frequency monitoring network deployed at distribution level. At first part of this thesis, FNET structure and characteristics are introduced. After analysis and smoothing FDR signals, the algorithm of event trigger is present with Visual C++ DLL programming. Estimation of disturbance location method is discussed based on the time delay of arriving (TDOA) in the second part of this work. In this section, author shows the multiply method to calculate event time, which is important when deal with pre-disturbance frequency in TDOA part. Two event kinds are classified by the change of frequency and the linear relationship between change of frequency and imbalance of generation and load power is presented. Prove that Time Delay of Arrival (TDOA) is a good algorithm for estimation event location proved by real cases. At last, the interface of DLL module and the key word to import and export DLL variables and function is described.

At last, PSS compensation optimization with a set of nonlinear differential algebraic equations (DAE) is introduced in detail. With combining the bifurcation theory of nonlinear system and the optimization theory, the optimal control of small-signal stability of power electric systems are solved. From the perspective of stability margin, global coordination of controller parameters is studied to ensure the stable operation of power grids. The main contents of this thesis include:

ï¼ 1ï¼ Models of power systems and test power electric systems. Tht5e dynamic and static models of the elements of power systems, such as generatorbbs, AVRs, PSSs, loads and FACTS controllers are presented. Method of power system linearization modeling is introduced. Three test power systems, WSCC 9-bus system, 2-area system, New England 39-bus system, are used in thesis.

ï¼ 2ï¼ Multi-objective optimizations based on bifurcation theory. The optimization models, damping control-Hopf bifurcation control, voltage control-damping control, are presented. Pareto combined with evolutionary strategy (ES) are used to solve multi-objective optimizations. Based on traditional PSS parameters optimizations, it can be formulated as a multi-objective problem, in which, two objectives should be taken into account. The minimum damping torque should be identified.
Master of Science

This thesis examines the relationship between investors' attention and movements in financial markets. Providing an explanation to the relationship between investor attention and market returns and return volatility, where attention is measured by Google search volume and two indirect price-based measures, investor attention does not contribute to return predictability however significant links to volatility are found. Furthermore, revisiting the joint volume-volatility relationship seeking to investigate the dynamic links of market volatility, trading volume, and investor attention (measured by Google search and Twitter tweet volume), investor attention provides a somewhat significant link for the rate at which investors seek market information.

[ES] Recientemente, hay una fuerte y creciente influencia de aplicaciones en línea en nuestro día a día. Más concretamente las redes sociales se cuentan entre las plataformas en línea más usadas, que permiten a usuarios comunicarse e interactuar desde diferentes partes del mundo todos los días. Dado que estas interacciones conllevan diferentes riesgos, y además los adolescentes tienen características que los hacen más vulnerables a ciertos riesgos, es deseable que el sistema pueda guiar a los usuarios cuando se encuentren interactuando en línea, para intentar mitigar la probabilidad de que caigan en uno de estos riesgos. Esto conduce a una experiencia en línea más segura y satisfactoria para usuarios de este tipo de plataformas. El interés en aplicaciones de inteligencia artificial capaces de realizar análisis de sentimientos ha crecido recientemente. Los usos de la detección automática de sentimiento de usuarios en plataformas en línea son variados y útiles. Se pueden usar polaridades de sentimiento para realizar minería de opiniones en personas o productos, y así descubrir las inclinaciones y opiniones de usuarios acerca de ciertos productos (o ciertas características de ellos), para ayudar en campañas de marketing, y también opiniones acerca de personas como políticos, para descubrir la intención de voto en un periodo electoral, por ejemplo. En esta tesis, se presenta un Sistema Multi-Agente (SMA), el cual integra agentes que realizan diferentes análisis de sentimientos y de estrés usando texto y dinámicas de escritura (usando análisis unimodal y multimodal), y utiliza la respuesta de los analizadores para generar retroalimentación para los usuarios y potencialmente evitar que caigan en riesgos y difundan comentarios en plataformas sociales en línea que pudieran difundir polaridades de sentimiento negativas o niveles altos de estrés. El SMA implementa un análisis en paralelo de diferentes tipos de datos y generación de retroalimentación a través del uso de dos mecanismos diferentes. El primer mecanismo se trata de un agente que realiza generación de retroalimentación y guiado de usuarios basándose en un conjunto de reglas y la salida de los analizadores. El segundo mecanismo es un módulo de Razonamiento Basado en Casos (CBR) que usa no solo la salida de los analizadores en los mensajes del usuario interactuando para predecir si su interacción puede generar una futura repercusión negativa, sino también información de contexto de interacciones de usuarios como son los tópicos sobre los que hablan o información sobre predicciones previas en mensajes escritos por la gente que conforma la audiencia del usuario. Se han llevado a cabo experimentos con datos de una red social privada generada en laboratorio con gente real usando el sistema en tiempo real, y también con datos de Twitter.com para descubrir cuál es la eficacia de los diferentes analizadores implementados y del módulo CBR al detectar estados del usuario que se propagan más en la red social. Esto conlleva descubrir cuál de las técnicas puede prevenir mejor riesgos potenciales que los usuarios pueden sufrir cuando interactúan, y en qué casos. Se han encontrado diferencias estadísticamente significativas y la versión final del SMA incorpora los analizadores que mejores resultados obtuvieron, un agente asesor o guía basado en reglas y un módulo CBR. El trabajo de esta tesis pretende ayudar a futuros desarrolladores de sistemas inteligentes a crear sistemas que puedan detectar el estado de los usuarios interactuando en sitios en línea y prevenir riesgos que los usuarios pudiesen enfrentar. Esto propiciaría una experiencia de usuario más segura y satisfactoria.
[CA] Recentment, hi ha una forta i creixent influència d'aplicacions en línia en el nostre dia a dia, i concretament les xarxes socials es compten entre les plataformes en línia més utilitzades, que permeten a usuaris comunicar-se i interactuar des de diferents parts del món cada dia. Donat que aquestes interaccions comporten diferents riscos, i a més els adolescents tenen característiques que els fan més vulnerables a certs riscos, seria desitjable que el sistema poguera guiar als usuaris mentre es troben interactuant en línia, per així poder mitigar la probabilitat de caure en un d'aquests riscos. Açò comporta una experiència en línia més segura i satisfactòria per a usuaris d'aquest tipus de plataformes. L'interés en aplicacions d'intel·ligència artificial capaces de realitzar anàlisi de sentiments ha crescut recentment. Els usos de la detecció automàtica de sentiments en usuaris en plataformes en línia són variats i útils. Es poden utilitzar polaritats de sentiment per a realitzar mineria d'opinions en persones o productes, i així descobrir les inclinacions i opinions d'usuaris sobre certs productes (o certes característiques d'ells), per a ajudar en campanyes de màrqueting, i també opinions sobre persones com polítics, per a descobrir la intenció de vot en un període electoral, per exemple. En aquesta tesi, es presenta un Sistema Multi-Agent (SMA), que integra agents que implementen diferents anàlisis de sentiments i d'estrés utilitzant text i dinàmica d'escriptura (utilitzant anàlisi unimodal i multimodal), i utilitza la resposta dels analitzadors per a generar retroalimentació per als usuaris i potencialment evitar que caiguen en riscos i difonguen comentaris en plataformes socials en línia que pogueren difondre polaritats de sentiment negatives o nivells alts d'estrés. El SMA implementa una anàlisi en paral·lel de diferents tipus de dades i generació de retroalimentació a través de l'ús de dos mecanismes diferents. El primer mecanisme es tracta d'un agent que realitza generació de retroalimentació i guia d'usuaris basant-se en un conjunt de regles i l'eixida dels analitzadors. El segon mecanisme és un mòdul de Raonament Basat en Casos (CBR) que utilitza no solament l'eixida dels analitzadors en els missatges de l'usuari per a predir si la seua interacció pot generar una futura repercussió negativa, sinó també informació de context d'interaccions d'usuaris, com són els tòpics sobre els quals es parla o informació sobre prediccions prèvies en missatges escrits per la gent que forma part de l'audiència de l'usuari. S'han realitzat experiments amb dades d'una xarxa social privada generada al laboratori amb gent real utilitzant el sistema implementat en temps real, i també amb dades de Twitter.com per a descobrir quina és l'eficàcia dels diferents analitzadors implementats i del mòdul CBR en detectar estats de l'usuari que es propaguen més a la xarxa social. Açò comporta descobrir quina de les tècniques millor pot prevenir riscos potencials que els usuaris poden sofrir quan interactuen, i en quins casos. S'han trobat diferències estadísticament significatives i la versió final del SMA incorpora els analitzadors que millors resultats obtingueren, un agent assessor o guia basat en regles i un mòdul CBR. El treball d'aquesta tesi pretén ajudar a futurs dissenyadors de sistemes intel·ligents a crear sistemes que puguen detectar l'estat dels usuaris interactuant en llocs en línia i prevenir riscos que els usuaris poguessen enfrontar. Açò propiciaria una experiència d'usuari més segura i satisfactòria.
[EN] In the present days, there is a strong and growing influence of on-line applications in our daily lives, and concretely Social Network Sites (SNSs) are one of the most used on-line social platforms that allow users to communicate and interact from different parts of the world every day. Since this interaction poses several risks, and also teenagers have characteristics that make them more vulnerable to certain risks, it is desirable that the system could be able to guide users when interacting on-line, to try and mitigate the probability of incurring one of those risks. This would in the end lead to a more satisfactory and safe experience for the users of such on-line platforms. Recently, interest in artificial intelligence applications being able to perform sentiment analysis has risen. The uses of detecting the sentiment of users in on-line platforms or sites are variated and rewarding. Sentiment polarities can be used to perform opinion mining on people or products, and discover the inclinations and opinions of users on certain products (or certain features of them) to help marketing campaigns, and also on people such as politics, to discover the voting intention for example in electoral periods. In this thesis, a Multi-Agent System (MAS) is presented, which integrates agents that perform different sentiment and stress analyses using text and keystroke dynamics data (using both unimodal and multi-modal analysis). The MAS uses the output of the analyzers for generating feedback for users and potentially avoids them from incurring risks and spreading comments in on-line social platforms that could lead to the spread of negative sentiment or high-stress levels. Moreover, the MAS incorporates parallelized analyses of different data types and feedback generation via the use of two different mechanisms. On the one hand, a rule-based advisor agent has been implemented, that generates feedback or guiding for users based on the output of the analyzers and a set of rules. On the other hand, a Case-Based Reasoning (CBR) module that uses not only the output of the different analyzers on the messages of the user interacting, but also context information from user interactions such as the topics being talked about or information about the previous states detected on messages written by people in the audience of the user. Experiments with data from a private SNS generated in a laboratory with real people using the system in real-time, and also with data from Twitter.com have been performed to ascertain the efficacy of the different analyzers implemented and the CBR module on detecting states of the user that propagate more in the network, which leads to discovering which of the techniques is able to better prevent potential risks that users could face when interacting, and in which cases. Significant differences were found and the final version of the MAS incorporates the best-performing analyzer agents, a rule-based advisor agent, and a CBR module. In the end, this thesis aims to help intelligent systems developers to build systems that are able to detect the state of users interacting in on-line sites and prevent risks that they could face, leading to a more satisfactory and safe user experience.
This thesis was funded by the following research projects: Privacy in Social Educational Environments during Child-hood and Adolescence (PESEDIA), Ministerio de Economia y Empresa (TIN2014-55206-R) and Intelligent Agents for Privacy Advice in Social Networks (AI4PRI), Ministerio de Economia y Empresa (TIN2017-89156-R)
Aguado Sarrió, G. (2021). MAS-based affective state analysis for user guiding in on-line social environments [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/164902
TESIS

The voltage profile of the catenary between traction substations (TSSs) is affected by the trolleybus current intake and by its position with respect to the TSSs: the higher the current requested by the bus and the further the bus from the TSSs, the deeper the voltage drop. When the voltage drops below 500V, the trolleybus is forced to decrease its consumption by reducing its input current. This thesis deals with the analysis of the improvements that the installation of an BESS produces in the operation of a particularly loaded FS of the DC trolleybus network of the city of Bologna. The stationary BESS is charged by the TSSs during off-peak times and delivers the stored energy when the catenary is overloaded alleviating the load on the TSSs and reducing the voltage drops. Only IMC buses are considered in the prospect of a future disposal of all internal combustion engine vehicles. These trolleybuses cause deeper voltage drops because they absorb enough current to power their traction motor and recharge the on board battery. The control of the BESS aims to keep the catenary voltage within the admissible voltage range and makes sure that all physical limitations are met. A model of FS Marconi Trento Trieste is implemented in Simulink environment to simulate its daily operation and compare the behavior of the trolleybus network with and without BESS. From the simulation without BESS, the best location of the energy storage system is deduced, and the battery control is tuned. Furthermore, from the knowledge of the load curve and the battery control trans-characteristic, it is formulated a prediction of the voltage distribution at BESS connection point. The prediction is then compared with the simulation results to validate the Simulink model. The BESS allows to decrease the voltage drops along the catenary, the Joule losses and the current delivered by the TSSs, indicating that the BESS can be a solution to improve the operation of the trolleybus network.

Quels seront les objectifs et défis des métropoles de demain ? La plupart des problèmes issus du monde réel sont sujets à l'inconnu, nécessitant de prendre de nouvelles décisions de façon dynamique, à la demande, en fonction des évènements aléatoires qui se réalisent. Dans cette thèse, nous nous attaquons à un problème majeur, du moins en perspectives: la gestion dynamique d'une flotte de véhicules en contexte urbain. Les applications pratiques des tournées de véhicules à la demande sont nombreuses, incluant les transports publics intelligents, les services de livraison, les soins et interventions à domicile, etc. Étant donnés une flotte de véhicules et un ensemble de clients, chacun pouvant potentiellement et à tout moment émettre une requête nécessitant une intervention, l'objectif de cette thèse est de fournir une réponse à la question suivante. Étant donné l'état courant à un moment donné, comment gérer notre flotte de véhicules afin de maximiser l'espérance du nombre total de requêtes satisfaites à la fin de la journée ? Ou encore, comment minimiser l'espérance du délai moyen d'intervention de nos véhicules ? Bien entendu, la difficulté réside en ce que la plupart des requêtes, avant d'apparaître dynamiquement, ne sont pas connues. Pour chaque problème, nous considérons qu'il nous est fourni une connaissance, sous forme d'information probabiliste, telle que la probabilité qu'une requête apparaisse à un certain endroit, et à un certain moment de la journée. Grâce à des techniques issues de la recherche opérationnelle et de la programmation stochastique, nous sommes en mesure de construire et résoudre des modèles calculant les actions anticipatives les plus adéquates, comme le redéploiement préventif des véhicules, minimisant le coût total espéré, ou encore maximisant la qualité de service. La question de l'optimisation sous incertitude se pose depuis déjà plusieurs décennies. Grâce aux avancées à la fois théoriques et technologiques, nous sommes chaque jour un peu plus en mesure de palier à l'inconnu. Cependant, la plupart des problèmes intéressants restent extrêmement difficiles à résoudre, si ce n'est impossible. Il reste beaucoup à faire. Cette thèse explore certains concepts fondamentaux de l'optimisation sous incertitude. En intégrant une composante stochastique aux modèles à optimiser, nous verrons ensemble comment il est en effet possible de créer de l'anticipation
What will be tomorrow's big cities objectives and challenges? Most of the operational problems from the real world are inherently subject to uncertainty, requiring the decision system to compute new decisions dynamically, as random events occur. In this thesis, we aim at tackling an important growing problem in urban context: online dynamic vehicle routing. Applications of online vehicle routing in the society are manyfold, from intelligent on demand public transportation to sameday delivery services and responsive home healthcare. Given a fleet of vehicles and a set of customers, each being potentially able to request a service at any moment, the current thesis aims at answering the following question. Provided the current state at some moment of the day, which are the best vehicle actions such that the expected number of satisfied requests is maximized by the end of the operational day? How can we minimize the expected average intervention delays of our mobile units? Naturally, most of the requests remain unknown until they appear, hence being revealed online. We assume a stochastic knowledge on each operational problem we tackle, such as the probability that customer request arise at a given location and a given time of the day. By using techniques from operations research and stochastic programming, we are able to build and solve mathematical models that compute near-optimal anticipative actions, such as preventive vehicle relocations, in order to either minimize the overall expected costs or maximize the quality of service. Optimization under uncertainty is definitely not a recent issue. Thanks to evolution of both theoretical and technological tools, our ability to face the unknown constantly grows. However, most of the interesting problems remain extremely hard, if not impossible, to solve. There is still a lot of work. Generally speaking, this thesis explores some fundamentals of optimization under uncertainty. By integrating a stochastic component into the models to be optimized, we will see how it is in fact possible to create anticipation

碩士
國立交通大學
工業工程與管理系所
102
This study consider that in wireless mesh networks (WMNs), mesh routers transmit multiple packets to the mesh clients with a long distance. Our design for the WMN model aims at transmitting packets to mesh clients within a given time limit. There have been plenty types of WMNs models for different targets, among which the WMN link scheduling model attempts to achieve the goal that can transmit packets efficiently by programming the open-and-shut control of links in WMNs under multi- ple real-world constrains. At first, this study refers many different conventional link scheduling models in WMNs, compares their characteristics, and inspects the algo- rithms that was used to schedule these models, respectively. Next, this study attempts to design a link scheduling model that contains more characteristics of WMNs in the realistic circumstance. This model puts the programming information on a more cor- rect position and has the design of gateways that can connect WMNs to Internet. After completing the new link scheduling model, this study adopts some algorithms which have showed superior performance over the other link scheduling models such as dy- namic programming (DP) and some heuristic algorithms. According to the experiment results, our scheduling model not only can contain several characteristics of WMNs but also can let the above-mentioned algorithms operate efficiently. Among these al- gorithms, approximate dynamic programming (ADP) can simulate the performance of DP efficiently and have a better performance than genetic algorithm (GA). When we extend the scale of our WMNs model, we use ADP to replace dynamic programming due to the concern of computational complexity. According to the experiment results, ADP still shows a superior performance than GA.

The most significant challenge for next wireless generation is to work opportunistically on the spectrum without a fixed spectrum allocation. Cognitive Radio (CR) is the candidate technology to utilize spectrum white space, which requires the CR to change its operating channel as the white space moves. In a CR ad-hoc network, each node could tune to a different channel; as a result, it cannot communicate with other nodes. This different tuning is due to the difficulty of maintaining Common Control Channel (CCC) in opportunistic spectrum network, and keeping the nodes synchronized in ad-hoc network. The CR ad-hoc network requires a protocol to match tuning channels between ad-hoc nodes, namely, rendezvous channels. In this thesis, two distributed Medium Access Control (MAC) protocols are designed that provide proper rendezvous channel without CCC or synchronization. The Balanced Incomplete Block Design (BIBD) is used in both protocols to provide our protocols a method of rendezvous between CR ad-hoc nodes. In fact, the BIBD guarantees there is at least one common element between any two blocks. If the channels are assigned to the BIBD elements and the searching sequence to the BIBD block, there is a guarantee of a rendezvous at least in one channel for each searching sequence. The first protocol uses a single-BIBD sequence and a multi-channel sensing. Alternatively, the second protocol uses a multi-BIBD sequence and a single-channel sensing. The single-sequence protocol analysis is based on the discrete Markov Chain. At the same time, the sequence structure of the BIBD in a multi-sequence protocol is used to define the Maximum Time to Rendezvous (MTTR). The simulation results confirm that the protocols outperform other existing protocols with respect to Time to Rendezvous (TTR), channel utilization, and network throughput. In addition, both protocols fairly distribute the network load on channels, and share the channels fairly among network nodes. This thesis provides straight forward and efficiently distributed MAC protocols for the CR ad-hoc networks.

Mesh network is gaining importance as the next generation network for many high speed applications such as multimedia streaming. This is because it is easy and inexpensive to setup mesh networks with mobile and PDA devices and can be used as a private network. Hence research is active in the field of routing protocols and routing metrics to improve the mesh network performance. Though most of the protocols are evaluated based on simulation, we implemented protocols based on a few metrics like Expected Transmission Count (ETX) Per-hop Packet Pair Delay (Pkt Pair) and WCETT (Weighted Cumulative Expected Transmitted Time) to investigate the performance of the network through experiments. An advanced version of DSR protocol called LQSR (Link Quality Source Routing) protocol of Microsoft Research along with MCL (Mesh Connectivity Layer) allows multiple heterogeneous adapters to be used in mesh network. Since wireless adapters of 802.11a standard offer 12 non-interfering channels and 802.11b/g standard offer 3 non-interfering channels, using multiple adapters of different bands operating on non-interfering channels to improve capacity and robustness of mesh networks was also investigated. In this thesis we explore the possibility of increasing the coverage area of Wireless Mesh Networks (WMN) to enhance the capacity of WMN and minimize the problems due to interference. Theoretical achievable capacity to every node in a random static wireless ad-hoc network with ideal routing is known to be where n is the total number of nodes in the network. Therefore, with increasing number of nodes in a network, throughput drops significantly. Our measurements show that throughput in a single WMN for different path length is closer to the throughput with nodes across two WMNs of the same path length. We propose to interconnect the networks by using multiple wireless adapters in a gateway node configured with the SSID of the networks in operation. We exploit the DSR protocol feature of assigning locally unique interface indices to its adapters. Performance of a network depends heavily on the metrics used for routing packets. Different metrics were studied in the thesis by setting up a 10-node testbed with a combination of nodes with single and two radios. Testbed was partitioned into two networks with two gateway nodes. Performance of multi-radio performance with the above metrics was compared with baseline single radio nodes in the network with the same metric. It is found that multi-radio nodes out-perform single radio nodes in the multi-hop scenario. Also, operating multi-mesh networks using multiple interfaces configured to those networks in a gateway node increases the coverage area and robustness without loss of performance.