Studying recurrent mobility perturbations, such as traffic congestions, is a major concern of engineers, planners, and authorities as they not only bring about delay and inconvenience but also have consequent negative impacts like greenhouse gas emission, increase in fuel consumption, or safety issues. In this dissertation, we proposed using the resilience concept, which has been commonly used for assessing the impact of extreme events and disturbances on the transportation system, for high-probability low impact (HPLI) events to (a) provide a performance assessment framework for transportation systems' response to traffic congestions, (b) investigate the role of transit modes in the resilience of urban roadways to congestion, and (c) study the impact of network topology on the resilience of roadways functionality performance. We proposed a multi-dimensional approach to characterize the resilience of urban transportation roadways for recurrent congestions. The resilience concept could provide an effective benchmark for comparative performance and identifying the behavior of the system in the discharging process in congestion. To this end, we used a Data Envelopment Analysis (DEA) approach to integrate multiple resilience-oriented attributes to estimate the efficiency (resilience) of the frontier in roadways. Our results from an empirical study on California highways through the PeMS data have shown the potential of the multi-dimensional approach in increasing information gain and differentiating between the severity of congestion across a transportation network. Leveraging this resilience-based characterization of recurrent disruptions, in the second study, we investigated the role of multi-modal resourcefulness of urban transportation systems, in terms of diversity and equity, on the resilience of roadways to daily-based congestions. We looked at the physical infrastructure availability and distribution (i.e. diversity) and accessibility and coverage to capture socio-economic factors (i.e. equity) to more comprehensively understand the role of resourcefulness in resilience. We conducted this investigation by using a GPS dataset of taxi trips in the Washington DC metropolitan area in 2017. Our results demonstrated the strong correlation of trips' resilience with transportation equity and to a lesser extent with transportation diversity. Furthermore, we learned the impact of equity and diversity can mostly be seen at the recovery stage of resilience. In the third study, we looked at another aspect of transportation supply in urban areas, spatial configuration, and topology. The goal of this study was to investigate the role of network topology and configuration on resilience to congestion. We used OSMnx, a toolkit for street network analysis based on the data from OpenStreetMap, to model and analyze the urban roadways network configurations. We further employed a multidimensional visualization strategy using radar charts to compare the topology of street networks on a single graphic. Leveraging the geometric descriptors of radar charts, we used the compactness and Jaccard Index to quantitatively compare the topology profiles. We use the same taxi trips dataset used in the second study to characterize resilience and identify the correlation with network topology. The results indicated a strong correlation between resilience and betweenness centrality, diameter, and Page Rank among other features of a transportation network. We further looked at the capacity of roadways as a common cause for the strong correlation between network features and resilience. We found that the strong correlation of link-related features such as diameter could be due to their role in capacity and have a common cause with resilience. / Doctor of Philosophy / Transportation infrastructure systems are among the most fundamental facilities and systems in urban areas due to the role they play in mobility, economy, and environmental sustainability. Due to this importance, it is crucial to ensure their resilience to regular disruptions such as traffic congestions as a priority for engineers and policymakers. The resilience of transportation systems has often been studied when disasters or extreme events occur. However, minor disturbances such as everyday operational traffic situations can also play an important part in reducing the efficiency of transportation systems and should be considered in the overall resilience of the systems. Current literature does not consider traffic performance from the lens of resilience despite its importance in evaluating the overall performance of roads. This research addresses this gap by proposing to leverage the concept of resilience for evaluation of roadways performance and identifying the role of urban characteristics in the enhancement of resilience. We first characterized resilience considering the performance of the roadways over time, ranging from the occurrence of disruptions to the time point when the system performance returns to a stable state. Through a case study on some of the major highways in the Los Angeles metropolitan area and by leveraging the data from the Performance Measurement System (PeMS), we have investigated how accounting for a proposed multi-dimensional approach for quantification of resilience could add value to the process of road network performance assessment and the corresponding decision-making. In the second and third parts of this dissertation, we looked at the urban infrastructure elements and how they affect resilience to regular disruptive congestion events. Specifically, in the second study, we focused on alternative transit modes such as bus, metro, or bike presence in the urban areas. We utilized diversity and equity concepts for assessing the opportunities they provide for people as alternative mobility modes. The proposed metrics not only capture the physical attributes of the multi-modal transportation systems (i.e. availability and distribution of transit modes in urban areas) but also consider the socio-economic factors (i.e. the number of people that could potentially use the transit mode). In the third study, we investigated how urban road networks' form and topology (i.e., the structure of roadway networks) could affect its resilience to recurrent congestions. We presented our findings as a case study in the Washington DC area. Results indicated a strong correlation between resilience and resourcefulness as well as topology features. The findings allow decision-makers to make more informed design and operational decisions and better incorporate the urban characteristics during the priority setting process.

The aim of this diploma thesis is to analyze, design and create the architecture of the WSageNt system web interface. The main focus of the system will be traffic monitoring and topology control of the network. The work describes basic technologies, design principles and implementation methods.

Le consensus des systèmes multi-agents a eu une attention considérable au cours de la dernière décennie. Le consensus est un processus coopératif dans lequel les agents interagissent afin de parvenir à un accord. La plupart des études se sont engagés à l'analyse de l'état d'équilibre du comportement de ce processus. Toutefois, au cours de la transitoire de ce processus une énorme quantité de données est produite. Dans cette thèse, notre objectif est d'exploiter les données produites au cours de la transitoire d'algorithmes de consensus moyenne asymptotique afin de concevoir des protocoles de consensus moyenne en temps fini, évaluer la robustesse du graphique, et éventuellement récupérer la topologie du graphe de manière distribuée. Le consensus de moyenne en temps fini garantit un temps d'exécution minimal qui peut assurer l'efficacité et la précision des algorithmes distribués complexes dans lesquels il est impliqué. Nous nous concentrons d'abord sur l'étape de configuration consacrée à la conception de protocoles de consensus qui garantissent la convergence de la moyenne exacte dans un nombre donné d'étapes. En considérant des réseaux d'agents modélisés avec des graphes non orientés connectés, nous formulons le problème de la factorisation de la matrice de moyenne et étudions des solutions distribuées à ce problème. Puisque, les appareils communicants doivent apprendre leur environnement avant d'établir des liens de communication, nous suggérons l'utilisation de séquences d'apprentissage afin de résoudre le problème de la factorisation. Ensuite, un algorithme semblable à l'algorithme de rétro-propagation du gradient est proposé pour résoudre un problème d'optimisation non convexe sous contrainte. Nous montrons que tout minimum local de la fonction de coût donne une factorisation exacte de la matrice de moyenne. En contraignant les matrices de facteur à être comme les matrices de consensus basées sur la matrice laplacienne, il est maintenant bien connu que la factorisation de la matrice de moyenne est entièrement caractérisé par les valeurs propres non nulles du laplacien. Par conséquent, la résolution de la factorisation de la matrice de la moyenne de manière distribuée avec une telle contrainte sur la matrice laplacienne, permet d'estimer le spectre de la matrice laplacienne. Depuis le spectre peut être utilisé pour calculer des indices de la robustesse (Nombre d'arbres couvrant et la résistance effective du graphe), la deuxième partie de cette thèse est consacrée à l'évaluation de la robustesse du réseau à travers l'estimation distribuée du spectre du Laplacien. Le problème est posé comme un problème de consensus sous contrainte formulé de deux façons différentes. La première formulation (approche directe) cède à un problème d'optimisation non-convexe résolu de manière distribuée au moyen de la méthode des multiplicateurs de Lagrange. La seconde formulation (approche indirecte) est obtenue après une reparamétrisation adéquate. Le problème est alors convexe et résolu en utilisant l'algorithme du sous-gradient distribué et la méthode de direction alternée de multiplicateurs. En outre, trois cas sont considérés: la valeur moyenne finale est parfaitement connue, bruyant, ou complètement inconnue. Nous fournissons également une façon pour calculer les multiplicités des valeurs propres estimées au moyen d'une programmation linéaire en nombres entiers. L'efficacité des solutions proposées est évaluée au moyen de simulations. Cependant, dans plusieurs cas, la convergence des algorithmes proposés est lente et doit être améliorée dans les travaux futurs. En outre, l'approche indirecte n'est pas évolutive pour des graphes de taille importante car elle implique le calcul des racines d'un polynôme de degré égal à la taille du réseau. Cependant, au lieu d'estimer tout le spectre, il peut être possible de récupérer seulement un petit nombre des valeurs propres, puis déduire des limites significatives sur les indices de la robustesse. / Consensus of Multi-agent systems has received tremendous attention during the last decade. Consensus is a cooperative process in which agents interact in order to reach an agreement. Most of studies are committed to analysis of the steady-state behavior of this process. However, during the transient of this process a huge amount of data is produced. In this thesis, our aim is to exploit data produced during the transient of asymptotic average consensus algorithms in order to design finite-time average consensus protocols, assess the robustness of the graph, and eventually recover the topology of the graph in a distributed way. Finite-time Average Consensus guarantees a minimal execution time that can ensure the efficiency and the accuracy of sophisticated distributed algorithms in which it is involved. We first focus on the configuration step devoted to the design of consensus protocols that guarantee convergence to the exact average in a given number of steps. By considering networks of agents modelled with connected undirected graphs, we formulate the problem as the factorization of the averaging matrix and investigate distributed solutions to this problem. Since, communicating devices have to learn their environment before establishing communication links, we suggest the usage of learning sequences in order to solve the factorization problem. Then a gradient backpropagation-like algorithm is proposed to solve a non-convex constrained optimization problem. We show that any local minimum of the cost function provides an accurate factorization of the averaging matrix. By constraining the factor matrices to be as Laplacian-based consensus matrices, it is now well known that the factorization of the averaging matrix is fully characterized by the nonzero Laplacian eigenvalues. Therefore, solving the factorization of the averaging matrix in a distributed way with such Laplacian matrix constraint allows estimating the spectrum of the Laplacian matrix. Since that spectrum can be used to compute some robustness indices (Number of spanning trees and Effective graph Resistance also known as Kirchoff index), the second part of this dissertation is dedicated to Network Robustness Assessment through distributed estimation of the Laplacian spectrum. The problem is posed as a constrained consensus problem formulated in two ways. The first formulation (direct approach) yields a non-convex optimization problem solved in a distributed way by means of the method of Lagrange multipliers. The second formulation (indirect approach) is obtained after an adequate re-parameterization. The problem is then convex and solved by using the distributed subgradient algorithm and the alternating direction method of multipliers. Furthermore, three cases are considered: the final average value is perfectly known, noisy, or completely unknown. We also provide a way for computing the multiplicities of the estimated eigenvalues by means of an Integer programming. In this spectral approach, given the Laplacian spectrum, the network topology can be reconstructed through estimation of Laplacian eigenvector. The efficiency of the proposed solutions is evaluated by means of simulations. However, in several cases, convergence of the proposed algorithms is slow and needs to be improved in future works. In addition, the indirect approach is not scalable to very large graphs since it involves the computation of roots of a polynomial with degree equal to the size of the network. However, instead of estimating all the spectrum, it can be possible to recover only a few number of eigenvalues and then deduce some significant bounds on robustness indices.

L'objectif de cette thèse est de fournir une évaluation de l'importance des caractéristiques du réseau bancaire pour expliquer la prise de décision des banques soumises à différents scénarios de politiques macroprudentielles et monétaires. Cette thèse examine donc les implications de la topologie des réseaux interbancaires pour la réglementation du capital et de la liquidité des banques et pour les politiques monétaires. Le premier chapitre examine comment les banques définissent leurs ratios de liquidité en fonction de la topologie de leur réseau sur le marché interbancaire. Nos résultats montrent que la prise en compte les connexions bancaires au sein d'un réseau améliore significativement les modèles de liquidité traditionnels. De plus, nous montrons que les banques fixent un ratio de liquidité plus bas lorsqu'elles ont un accès plus facile au marché interbancaire. Nos résultats soulignent également que le comportement en termes de liquidité des banques de tailles différentes ou des banques opérant dans différents systèmes bancaires pourrait varier en fonction de leurs positions interbancaires locales ou à l'échelle du système. Le deuxième chapitre analyse la réaction des prix des actions des banques aux annonces de politiques monétaires en fonction de leur position sur le marché interbancaire. Nos résultats montrent que la prise en compte de la manière dont les banques sont liées au sein d’un réseau contribue à l’explication de la réaction des prix de leurs actions à l’annonce des politiques monétaires. Nos résultats suggèrent qu'une position de réseau solide à l'échelle du système augmente les réactions positives à de telles annonces de politiques, alors qu'une position de réseau locale forte les réduit. Le troisième chapitre examine comment les effets de substitution de la liquidité sur le capital sont influencés par la position de la banque sur le marché interbancaire. Nous montrons que l’effet de substitution de la liquidité sur le capital est atténué si les banques sont fortement interconnectées dans le réseau interbancaire. Nos résultats suggèrent qu'en période de crise, les grandes banques non liquides détiennent un ratio de fonds propres élevé uniquement lorsqu'elles occupent une position faible sur le réseau interbancaire au niveau local ou à l'échelle du système, tandis que les petites banques non liquides renforcent leur solvabilité lorsqu'elles comptent un plus grand nombre d'emprunteurs directs . / The aim of this dissertation is to provide an evaluation of the importance of the bank network characteristics in explaining bank decision making under different macroprudential and monetary policy scenarios. This study examines, therefore, the implication of interbank network topology for bank capital and liquidity regulation and for monetary policies. The first chapter investigates how banks set their liquidity ratios depending on their network topology in the interbank market. Our results show that incorporating bank connections within a network adds value to traditional liquidity models. Moreover, we show that banks set lower liquidity ratios when they have easier access to the interbank market. Our findings also highlight that liquidity behavior of banks with different size, or banks that are operating in different banking sectors could vary depending on their local or system-wide interbank positions. The second chapter analyses the reaction of bank stock prices to the announcements of monetary policies depending on their position on the interbank market. Our results show that taking into account the way that banks are linked to each other within a network adds value to explain bank stock prices reaction to the announcement of monetary policies. Our findings suggest that strong system-wide network position increases the positive reactions to such policy announcements while strong local network position reduces them. The third chapter examines how the substitution effect of liquidity on capital are influenced by bank network position on the interbank market. We show that the substitution effect of liquidity on capital is dampened if banks are strongly interconnected in the interbank network. Our findings suggest that during crisis periods, illiquid large banks set higher capital ratio only when they have a weak local or system-wide position on the interbank network while illiquid small banks strengthen their solvency when they have a higher number of direct borrowers in that network.

<p>This thesis is an experimental study to evaluate the performance of different routing protocols in commonly deployed scenarios. This study mainly focuses on how much time each protocol consumes while recovering from a link-loss. It provides a guide line for the best routing solutions for ISPs, individual organizations or other types of providers which are engaged in providing reliable real-time communications to their subscribers. Such communications may include vehicle trafficking data, online TV programs (IPTV), voice over IP telephony (VoIP), weather forecasts, tracking systems and many other services which totally depend upon the reliability of real-time data streams, where any major loss in received data may bring significant negative results in the integrity of the entire application.</p><p>This work experimentally observes and tracks the loss of UDP packets when changes in the network topology occur. In order to make this observation in real network topologies, a custom-designed software tool has been developed. The tool is capable of delivering enough resources to a tester in evaluating the performance of routing protocols. All the test results derived from the software tool are statistically evaluated and on the basis of the outcome a better proposition can be provided to network administrators which face inconsistent topological issues.</p>

This thesis is an experimental study to evaluate the performance of different routing protocols in commonly deployed scenarios. This study mainly focuses on how much time each protocol consumes while recovering from a link-loss. It provides a guide line for the best routing solutions for ISPs, individual organizations or other types of providers which are engaged in providing reliable real-time communications to their subscribers. Such communications may include vehicle trafficking data, online TV programs (IPTV), voice over IP telephony (VoIP), weather forecasts, tracking systems and many other services which totally depend upon the reliability of real-time data streams, where any major loss in received data may bring significant negative results in the integrity of the entire application. This work experimentally observes and tracks the loss of UDP packets when changes in the network topology occur. In order to make this observation in real network topologies, a custom-designed software tool has been developed. The tool is capable of delivering enough resources to a tester in evaluating the performance of routing protocols. All the test results derived from the software tool are statistically evaluated and on the basis of the outcome a better proposition can be provided to network administrators which face inconsistent topological issues.

Wireless sensor networks (WSNs) are characterized by limited amount of energy supply at sensor nodes. Hence, energy efficiency is an important issue in system design and operation of WSNs. In this work we focus on solving the energy efficiency problems of data gathering processes in WSNs. We first address this problem on a macroscopic level by investigating the efficiency of data gathering trees when data sent by different sensors are correlated. Such correlation aware data gathering strategies typically shift the aggregation structure from a default shortest-path tree (SPT) to a steiner minimum tree (SMT) in order to achieve the required efficiency. We study the energy efficiency of correlation aware data aggregation trees under various sensor network conditions and the tradeoffs involved in using them. Comprehensive simulation results as well as inferences and theoretical analysis of those results are presented in the thesis. Based on the insights gained through the investigation, we propose a simple, scalable and distributed correlation aware aggregation structure that achieves good energy performance across a wide range of sensor network configurations, and at the same time addresses the practical challenges of establishing a correlation aware data aggregation structure in resource-constrained WSNs. On a microscopic level, we propose a novel communication strategy called Communication through Silence (CtS) to achieve energy-efficient data gathering without significant degradation on overall throughput in WSNs. The proposed scheme primarily uses time, along with a minimal amount of energy to deliver information among sensors. CtS can be used to replace the conventional energy-based transmissions between each pair of sensor nodes during a data gathering process. We analyze in detail the primary energy-throughput tradeoff inherent in this approach as well as other challenges related to the realization of the proposed communication strategy. Finally, we propose a practical realization of CtS strategy that includes radio technology, MAC layer, and higher layer solutions. Performance evaluation results prove that this solution effectively realizes the CtS strategy in a WSN setting, at the same time achieves considerable energy savings compared to conventional communication strategies.

Epidemic models help researchers understand and predict the nature of a potential epidemic. This study analyzes and improves network evolution technology that evolves contact networks so that simulated epidemics on the network mimic a specified epidemic pattern. The evolutionary algorithm incorporates the novel recentering-restarting algorithm, which is adopted into the optimizer to allow for efficient search of the space of networks. It also implements the toggle-delete representation which allows for broader search of solution space. Then, a diffusion character based method is used for analyzing the contact networks. A comparison of simulated epidemics that result from changing patient zero for a single contact network is performed. It is found that the location of patient zero is important for the behaviour of an epidemic. The social fabric representation is invented and then tested for parameter choices. The response to vaccination strategies (including ring vaccination) is then tested by incorporating them into the epidemic simulations. / Ontario Graduate Scholarship (OGS), Natural Sciences and Engineering Research Council of Canada (NSERC)

Disertacijoje nagrinėjama interneto tinklo infrastruktūros patikimumo problematika, analizei naudojant tinklo topologijos tyrimus, grafų teorijos taikymą ir tinklo modeliavimą. Tyrimų objektas, interneto tinklo infrastruktūra, kurios pagrindą sudaro autonominės sistemos ir tarptinklinių sujungimų linijos. Nuo stabilios interneto tinklo veiklos priklauso informacijos pasiekiamumas, elektroninė komercija, nutolusių objektų valdymas ir t. t. Pagrindinis disertacijos tikslas – sukurti metodikas ir algoritmus, skirtus interneto tinklo infrastruktūros analizei bei veiklos patikimumo kontrolei. Tyrimų taikymo sritis – interneto tinklo veiklos tęstinumo priežiūra ir reguliavimas. Darbe sprendžiami šie pagrindiniai uždaviniai: interneto tinklo topologijos analizės modelio ir priemonių sudarymas; interneto junglumo tyrimas siekiant identifikuoti kritinius elementus, kurių pažeidimai susiję su tinklo funkcionalumo praradimu; kritinių interneto tinklo elementų stebėsenos modelio sudarymas; eksperimentiniai kibernetinių atakų simuliacijos bandymai; bei interneto tinklo infrastruktūros patikimo stiprinimo parinkimas. Disertaciją sudaro įvadas, 5 skyriai, rezultatų apibendrinimas, naudotos literatūros ir autoriaus publikacijų disertacijos tema sąrašai bei priedai. / The dissertation investigates the issues of dependability of the Internet network infrastructure that were studied by using the network topology analysis, graph theory and network modelling. The object of the study is the Internet network infrastructure, based on autonomous systems and interconnecting lines. Stable functioning of the Internet network determines the availability of information, electronic commerce, control of remote objects, etc. The main objective is to develop the methodologies and algorithms for analysing the Internet network infrastructure and controlling the reliability of functioning. The scope of application of the study is the supervision and regulation of continuity of the Internet. The following main tasks are solved: development of the topological scheme of the Internet network, selection of models and tools for analysis; the Internet network connectivity analysis for the purpose of identification of the critical network elements, whose violations would result in loss of connectivity of the network; as well as development of the model for monitoring of the critical elements of the Internet network and cyber-attacks simulation experiments. The scientific work consists of the general characteristic of the dissertation, 5 chapters, conclusions, list of literature, list of publications and annexes.

The dissertation investigates the issues of dependability of the Internet network infrastructure that were studied by using the network topology analysis, graph theory and network modelling. The object of the study is the Internet network infrastructure, based on autonomous systems and interconnecting lines. Stable functioning of the Internet network determines the availability of information, electronic commerce, control of remote objects, etc. The main objective is to develop the methodologies and algorithms for analysing the Internet network infrastructure and controlling the reliability of functioning. The scope of application of the study is the supervision and regulation of continuity of the Internet. The following main tasks are solved: development of the topological scheme of the Internet network, selection of models and tools for analysis; the Internet network connectivity analysis for the purpose of identification of the critical network elements, whose violations would result in loss of connectivity of the network; as well as development of the model for monitoring of the critical elements of the Internet network and cyber-attacks simulation experiments. The scientific work consists of the general characteristic of the dissertation, 5 chapters, conclusions, list of literature, list of publications and annexes. / Disertacijoje nagrinėjama interneto tinklo infrastruktūros patikimumo problematika, analizei naudojant tinklo topologijos tyrimus, grafų teorijos taikymą ir tinklo modeliavimą. Tyrimų objektas, interneto tinklo infrastruktūra, kurios pagrindą sudaro autonominės sistemos ir tarptinklinių sujungimų linijos. Nuo stabilios interneto tinklo veiklos priklauso informacijos pasiekiamumas, elektroninė komercija, nutolusių objektų valdymas ir t. t. Pagrindinis disertacijos tikslas – sukurti metodikas ir algoritmus, skirtus interneto tinklo infrastruktūros analizei bei veiklos patikimumo kontrolei. Tyrimų taikymo sritis – interneto tinklo veiklos tęstinumo priežiūra ir reguliavimas. Darbe sprendžiami šie pagrindiniai uždaviniai: interneto tinklo topologijos analizės modelio ir priemonių sudarymas; interneto junglumo tyrimas siekiant identifikuoti kritinius elementus, kurių pažeidimai susiję su tinklo funkcionalumo praradimu; kritinių interneto tinklo elementų stebėsenos modelio sudarymas; eksperimentiniai kibernetinių atakų simuliacijos bandymai; bei interneto tinklo infrastruktūros patikimo stiprinimo parinkimas. Disertaciją sudaro įvadas, 5 skyriai, rezultatų apibendrinimas, naudotos literatūros ir autoriaus publikacijų disertacijos tema sąrašai bei priedai.