Unmanned aerial vehicle (UAV) networks, a flying platform, are a promising wireless communications infrastructure with wide-ranging applications in both commercial and military domain. Owing to the appealing characteristics, such as high mobility, high feasibility, and low cost, UAV networks can be applied in various scenarios, such as emergency communications, cellular networks, device-to-device (D2D) networks, and sensor networks, regardless of infrastructure and spatial constraints. To handle complicated missions, provide wireless coverage for a large range, and have a long lifetime, a UAV network may consist of a large amount of UAVs, working cooperatively as a swarm, also referred to as swarm UAV networks. Although high mobility and numerous UAVs offer high flexibility, high scalability, and performance enhancement for swarm UAV networks, they also incur some technical challenges. One of the major challenges is the routing protocol design. With high mobility, a dynamic network topology may be encountered. As a result, traditional routing protocols based on routing path discovery are not applicable in swarm UAV networks, as the discovered routing path may be outdated especially when the amount of UAVs is large causing considerable routing path discovery delay. Multicast is an essential and key technology in the scenarios, where swarm UAV networks are employed as aerial small base station (BSs), like relay or micro BS. Swarm UAV networks consisting of a large amount of UAVs will encounter severe multicast delay with existing multicast methods using acknowledgement (ACK) feedback and retransmissions. This issue will be deteriorated when a swarm UAV network is deployed far away from BSs, causing high packet loss. Data exchange is another major technical challenge in swarm UAV networks, where UAVs exchange data packets with each other, such as requesting and retrieving lost packets. Due to numerous UAVs, data exchange between UAVs can cause message and signaling storm, resulting in a long data exchange delay and severe ovehead. In this dissertation, I focus on developing novel routing protocols, multicast schemes, and data exchange schemes, enabling efficient, robust, and high-performance routing, multicast, and data exchange in swarm UAV networks. To be specific, two novel flooding-based routing protocols are designed in this dissertation, where random network coding (RNC) is utilized to improve the efficiency of the flooding-based routing in swarm UAV networks without relying on network topology information and routing path discovery. Using the property of RNC that as long as sufficient different versions of encoded packets/generations are accumulated, original packets could be decoded, RNC is naturally able to accelerate the routing process. This is because the use of RNC can reduce the number of encoded packets that are required to be delivered in some hop. In a hop, the receiver UAV may have already overheard some generations in previous hops, so that it only needs to receive fewer generations from the transmitter UAV in the current hop. To further expedite the flooding-based routing, the second flooding-based routing protocol is designed, where each forwarding UAV creates a new version of generation by linearly combining received generations rather than by decode original packets. Despite the flooding-based routing significantly hastened by RNC, the inherent drawback of the flooding-based routing is still unsolved, namely numerous hops. Aiming at reducing the amount of hops, a novel enhanced flooding-based routing protocol leveraging clustering is designed, where the whole UAV network will be partitioned into multiple clusters and in each cluster only one UAV will be selected as the representative of this cluster, participating in the flooding-based routing process. By this way, the number of hops is restricted by the number of representatives, since packets are only flooded between limited representatives rather than numerous UAVs. To address the multicast issue in swarm UAV networks, a novel multicast scheme is proposed based on clustering, where a UAV experiencing packet loss will retrieve the lost packets by requesting other UAVs in the same cluster without depending on retransmissions of BSs. In this way, the lost packet retrieval is carried out through short-distance data exchange between UAVs with reliable transmissions and a short delay. Tractable stochastic geometry tools are used to model swarm UAV networks with a dynamic network topology, based on which comprehensive analytical performance analysis is given. To enable efficient data exchange between UAVs in swarm UAV networks, a data exchange scheme is proposed utilizing unsupervised learning. With the proposed scheme, all UAVs are assigned to multiple clusters and a UAV can only carry out data exchange within its cluster. By this way, UAVs in different clusters perform data exchange in a parallel fashion to expedite data exchange. The agglomerative hierarchical clustering, a type of unsupervised learning, is used to conduct clustering in order to guarantee that UAVs in the same cluster are able to supply and supplement each other's lost packets. Additionally, a data exchange mechanism, including a novel random backoff procedure, is designed, where the priorities of UAVs in data exchange determined by the number of their lost packets or requested packets that they can provide. As a result, each request-reply process would be taken fully advantage, maximally supplying lost packets not only to the UAV sending request, but also to other UAVs in the same cluster. For all the developed technologies in this dissertation, their technical details and the corresponding system procedures are designed based on low-complexity and well-developed technologies, such as the carrier sense multiple access/collision avoidance (CSMA/CA), for practicability in practice and without loss of generality. Moreover, extensive simulation studies are conducted to demonstrate the effectiveness and superiority of the proposed and developed technologies. Additionally, system design insights are also explored and revealed through simulations. / Doctor of Philosophy / Compared to fixed infrastructures in wireless communications, unmanned aerial vehicle (UAV) networks possess some significant advantages, such as low cost, high mobility, and high feasibility, making UAV networks have a wide range of applications in both military and commercial fields. However, some characteristics of UAV networks, including dynamic network topology and numerous UAVs, may become technical barriers for wireless communications. One of the major challenges is the routing protocol design. Routing is the process of selecting a routing path, enabling data delivered from a node (source) to another desired node (destination). Traditionally, routing is performed based on routing path discovery, where control packets are broadcasted and the path, on which a control packet first reaches the destination, will be selected as routing path. However, in UAV networks, routing path discovery may experience a long delay, as control packets go through many UAVs. Besides, the discovered routing path may be outdated, as the topology of UAV networks change over time. Another key technology in wireless communications that may not work well in UAV networks is multicast, where a transmitter, like a base station (BS), broadcasts data to UAVs and all UAVs are required to receive this data. With numerous UAVs, multicast delay may be severe, since the transmitter will keep retransmitting a data packet to UAVs until all UAVs successfully receive the packet. This issue will be deteriorated when a UAV network is deployed far away from BSs, causing high packet loss. Data exchange between UAVs is a fundamental and important system procedure in UAV networks. A large amount of UAV in a UAV network will cause serious data exchange delay, as many UAVs have to compete for limited wireless resources to request or send data. In this dissertation, I focus on developing novel technologies and schemes for swarm UAV networks, where a large amount of UAVs exist to make UAV networks powerful and handle complicated missions, enable efficient, robust, and high-performance routing, multicast, and data exchange system procedures. To be specific, two novel flooding-based routing protocols are designed, where random network coding (RNC) is utilized to improve the efficiency of flooding-based routing without relying on any network topology information or routing path discovery. The use of RNC could naturally expedite flooding-based routing process. With RNC, a receiver can decode original packets as long as it accumulates sufficient encoded packets, which may be sent by different transmitters in different hops. As a result, in some hops, fewer generations may be required to be transmitted, as receivers have already received and accumulated some encoded in previous hops. To further improve the efficiency of flooding-based routing, another routing protocol using RNC is designed, where UAVs create new encoded packets by linearly combining received encoded packets rather than linearly combing original packets. Apparently, this method would be more efficient. UAVs do not need to collect sufficient encoded packets and decode original packets, while only linearly combining all received encoded packets. Although RNC could effectively improve the efficiency of flooding-based routing, the inherent drawback is still unsolved, which is a large amount of hops caused by numerous UAVs. Thus, an enhanced flooding-based routing protocol using clustering is designed, where the whole UAV network will be partitioned into multiple clusters. In each cluster only one UAV will be selected as the representative of this cluster, participating in the flooding-based routing process. By this way, the number of hops could be greatly reduced, as packets are only flooded between limited representatives rather than numerous UAVs. To address the multicast issue in swarm UAV networks, a novel multicast scheme is proposed, where a UAV experiencing packet loss will retrieve its lost packets by requesting other UAVs in the same cluster without depending on retransmissions of BSs. In this way, the lost packet retrieval is carried out through short-distance data exchange between UAVs with reliable transmissions and a short delay. Then, the optimal number of clusters and the performance of the proposed multicast scheme are investigated by tractable stochastic geometry tools. If all UAVs closely stay together in a swarm UAV network, long data exchange delay would be significant technical issue, since UAVs will cause considerable interference to each other and all UAVs will compete for spectrum access. To cope with that, a data exchange scheme is proposed leveraging unsupervised learning. To avoid interference between UAVs and a long-time waiting for spectrum access, all UAVs are assigned to multiple clusters and different clusters use different frequency bands to carry out data exchange simultaneously. The agglomerative hierarchical clustering, a type of unsupervised learning, is used to conduct clustering, guaranteeing that UAVs in the same cluster are able to supply and supplement each other's lost packets. Additionally, a data exchange mechanism is designed, facilitating that a UAV with more lost packets or more requested packets has a higher priority to carry out data exchange. In this way, each request-reply process would be taken fully advantage, maximally supplying lost packets not only to the UAV sending request, but also to other UAVs in the same cluster. For all the developed technologies in this dissertation, their technical details and the corresponding system procedures are designed based on low-complexity and well-developed technologies, such as the carrier sense multiple access/collision avoidance (CSMA/CA), for practicability in reality and without loss of generality. Moreover, extensive simulation studies are conducted to demonstrate the effectiveness and superiority of the developed technologies. Additionally, system design insights are also explored and revealed through simulations.

The development of autonomous ground and aerial vehicles has driven the requirement for radio access technologies (RATs) to support low latency applications. While onboard sensors such as Light Detection and Ranging (LIDAR), Radio Detection and Ranging (RADAR), and cameras can sense and assess the immediate space around the vehicle, RATs are crucial for the exchange of information on critical events, such as accidents and changes in trajectory, with other vehicles and surrounding infrastructure in a timely manner. Simulations and analytical models are critical in modelling and designing efficient networks. In this dissertation, we focus on (a) proposing and developing algorithms to improve the performance of decentralized vehicular communications in safety critical situations and (b) supporting these proposals with simulation and analysis of the two most popular RAT standards, the Dedicated Short Range Communications (DSRC) standard, and the Cellular vehicle-to-everything (C-V2X) standard. In our first contribution, we propose a risk based protocol for vehicles using the DSRC standard. The protocol allows a higher beacon transmission rate for vehicles that are at a higher risk of collision. We verify the benefits of the risk based protocol over conventional DSRC using ns-3 simulations. Two risk based beacon rate protocols are evaluated in our ns-3 simulator, one that adapts the beacon rate between 1 and 10 Hz, and another between 1 and 20 Hz. Our results show that both protocols improve the packet delivery ratio (PDR) performance by up to 45% in congested environments using the 1-10 Hz adaptive beacon rate protocol and by 38% using the 1-20 Hz adaptive scheme. The two adaptive beacon rate protocol simulation results also show that the likelihood of a vehicle collision due to missed packets decreases by up to 41% and 77% respectively, in a three lane dense highway scenario with 160 vehicles operating at different speeds. In our second contribution, we study the performance of a distance based transmission protocol for vehicular ad hoc network (VANET) using tools from stochastic geometry. We consider a risk based transmission protocol where vehicles transmit more frequently depending on the distance to adjacent vehicles. We evaluate two transmission policies, a listen more policy, in which the transmission rate of vehicles decreases as the inter-vehicular distance decreases, and a talk more policy, in which the transmission rate of vehicles increases as the distance to the vehicle ahead of it decreases. We model the layout of a highway using a 1-D Poisson Point process (PPP) and analyze the performance of a typical receiver in this highway setting. We characterize the success probability of a typical link assuming slotted ALOHA as the channel access scheme. We study the trends in success probability as a function of system parameters. Our third contribution includes improvements to the 3rd Generation Partnership Project (3GPP) Release 14 C-V2X standard, evaluated using a modified collision framework. In C-V2X basic safety messages (BSMs) are transmitted through Mode-4 communications, introduced in Release 14. Mode-4 communications operate under the principle of sensing-based semi-persistent scheduling (SPS), where vehicles sense and schedule transmissions without a base station present. We propose an improved adaptive semi-persistent scheduling, termed Ch-RRI SPS, for Mode-4 C-V2X networks. Specifically, Ch-RRI SPS allows each vehicle to dynamically adjust in real-time the BSM rate, referred to in the LTE standard as the resource reservation interval (RRI). Our study based on system level simulations demonstrates that Ch-RRI SPS greatly outperforms SPS in terms of both on-road safety performance, measured as collision risk, and network performance, measured as packet delivery ratio, in all considered C-V2X scenarios. In high density scenarios, e.g., 80 vehicles/km, Ch-RRI SPS shows a collision risk reduction of 51.27%, 51.20% and 75.41% when compared with SPS with 20 ms, 50 ms, and 100 ms RRI respectively. In our fourth and final contribution, we look at the tracking error and age-of-information (AoI) of the latest 3GPP Release 16 NR-V2X standard, which includes enhancements to the 3GPP Release 14 C-V2X standard. The successor to Mode-4 C-V2X, known as Mode-2a NR-V2X, makes slight changes to sensing-based semi-persistent scheduling (SPS), though vehicles can still sense and schedule transmissions without a base station present. We use AoI and tracking error, which is the freshness of the information at the receiver and the difference in estimated vs actual location of a transmitting vehicle respectively, to measure the impact of lost and outdated BSMs on a vehicle's ability to localize neighboring vehicles. In this work, we again show that such BSM scheduling (with a fixed RRI) suffers from severe under- and over- utilization of radio resources, which severely compromises timely dissemination of BSMs and increases the system AoI and tracking error. To address this, we propose an RRI selection algorithm that measures the age or freshness of messages from neighboring vehicles to select an RRI, termed Age of Information (AoI)-aware RRI (AoI-RRI) selection. Specifically, AoI-aware SPS (i) measures the neighborhood AoI (as opposed to channel availability) to select an age-optimal RRI and (ii) uses a modified SPS procedure with the chosen RRI to select BSM transmission opportunities that minimize the overall system AoI. We compare AoI-RRI SPS to Ch-RRI SPS and fixed RRI SPS for NR-V2X. Our experiments based on the Mode-2a NR-V2X standard implemented using system level simulations show both Ch-RRI SPS and AoI-RRI SPS outperform SPS in high density scenarios in terms of tracking error and age-of-information. / Doctor of Philosophy / An increasing number of vehicles are equipped with a large set of on-board sensors that enable and support autonomous capabilities. Such sensors, which include Light Detection and Ranging (LIDAR), Radio Detection and Ranging (RADAR), and cameras, are meant to increase passenger and driver safety. However, similar to humans, these sensors are limited to line-of-sight (LOS) visibility, meaning they cannot see beyond other vehicles, corners, and buildings. For this reason, efficient vehicular communications are essential to the next generation of vehicles and could significantly improve road safety. In addition, vehicular communications enable the timely exchange of critical information with other vehicles, cellular and roadside infrastructure, and pedestrians. However, unlike typical wireless and cellular networks, vehicular networks are expected to operate in a distributed manner, as there is no guarantee of the presence of cellular infrastructure. Accurate simulations and analytical models are critical in improving and guaranteeing the performance of the next generation of vehicular networks. In this dissertation, we propose and develop novel and practical distributed algorithms to enhance the performance of decentralized vehicular communications. We support these algorithms with computer simulations and analytical tools from the field of stochastic geometry.

<p>U ovoj disertaciji razvijeni su analitički alati za izračunavanje protoka servisa, propusnog opsega i u&scaron;tede energije zahtevanim u različitim eMBMS LTE/LTE-A servisnim strukturama. Takođe, mi smo analizirali protok podataka i optimalnu dodelu parametara za prenos na fizičkom sloju za eMBMS baziran video servis u 2-klasnoj heterogenoj mreži primenom stohastičke geometrije.</p> / <p>In this dissertation we develop simple analytical tools for evaluation of average service data rates, bandwidth and energy consumption requirements in dierent eMBMS LTE/LTE-A service congurations. Also, we consider a simple approach to estimate achievable rates and optimally assign the physical layer transmission parameters for eMBMS based video service in the two-tier heterogeneous cellular systems.</p>

Title: Nonstacionary particle processes Author: Čeněk Jirsák Department: Department of Probability and Mathematical Statistics Supervisor: Doc. RNDr. Jan Rataj, CSc., Mathematical Institute, Charles University Supervisor's e-mail address: rataj@karlin.mff.cuni.cz Abstract: Many real phenomena can be modeled as random closed sets of different Hausdorff dimension in Rd . One of the main characteristics of such random set is its expected Hausdorff measure. In case that this measure has a density, the density is called intensity function. In present paper we define a nonparametric kernel estimation of the intensity function. The concept of Hk -rectifiable set has a key role here. Properties of kernel estimation such as unbiasness or convergence behavior are studied. As the esti- mation may be difficult to compute precisely numerical approximations are derived for practical use. Parametric models are also briefly mentioned and the kernel estimation is used with the minimum contrast method to estimate the parameters of the model. At last the suggested methods are tested on simulated data. Keywords: stochastic geometry, intensity measure, random closed set, kernel estimation 1

Managing interference is the main technical challenge in wireless networks. Multiple input multiple output (MIMO) methods are key components to overcome the interference bottleneck and deliver higher data rates. The most efficient MIMO techniques require channel state information (CSI). In practice, this information is inaccurate due to errors in CSI acquisition, as well as mobility and delay. CSI inaccuracy reduces the performance gains provided by MIMO. When compounded with uncoordinated intercell interference, the degradation in MIMO performance is accentuated. This dissertation investigates the impact of CSI inaccuracy on the performance of increasingly complex interference limited networks, starting with a single interferer scenario, continuing to a heterogeneous network with a femtocell overlay, and finishing with a clustered multicell coordination model for randomly deployed transmitting nodes. First, this dissertation analyzes limited feedback beamforming and precoded spatial multiplexing over temporally correlated channels. Assuming uncoordinated interference from one dominant interferer, using Markov chain convergence theory, the gain in the average successful throughput at the mobile user is shown to decrease exponentially with the feedback delay. The decay rate is amplified when the user is interference limited. Interference cancellation methods at the receiver are shown to mitigate the effect of interference. This work motivates the need for practical MIMO designs to overcome the adverse effects of interference. Second, limited feedback beamforming is analyzed on the downlink of a more realistic heterogeneous cellular network. Future generation cellular networks are expected to be heterogeneous, consisting of a mixture of macro base stations and low power nodes, to support the increasing user traffic capacity and reliability demand. Interference in heterogeneous environments cannot be coordinated using traditional interference mitigation techniques due to the on demand and random deployment of low power nodes such as femtocells. Using tools from stochastic geometry, the outage and average achievable rate of limited feedback MIMO is computed with same-tier and cross-tier interference, and feedback delay. A hybrid fixed and random network deployment model is used to analyze the performance in a fixed cell of interest. The maximum density of transmitting femtocells is derived as a function of the feedback rate and delay. The detrimental effect of same-tier interference is quantified, as the mobile user moves from the cell-center to the cell-edge. The third part of this dissertation considers limited coordination between randomly deployed transmitters. Building on the established degrading effect of uncoordinated interference on practical MIMO methods, and the analytical tractability of random deployment models, interference coordination is analyzed. Using multiple antennas at the transmitter for interference nulling in ad hoc networks is first shown to achieve MIMO gains using single antenna receivers. Clustered coordination is then investigated for cellular systems with randomly deployed base stations. As full coordination in the network is not feasible, a random clustering model is proposed where base stations located in the same cluster coordinate. The average achievable rate can be optimized as a function of the number of antennas to maximize the coordination gains. For multicell limited feedback, adaptive partitioning of feedback bits as a function of the signal and interference strength is proposed to minimize the loss in rate due to finite rate feedback. / text

Interference is a defining feature of a wireless network. How to optimally deal with it is one of the most critical and least understood aspects of decentralized multiuser communication. This dissertation focuses on distributed transmission strategies that a transmitter can follow to achieve reliability while reducing the impact of interference. The problem is investigated from three directions : distributed opportunistic scheduling, multicast outage and transmission capacity, and ergodic transmission capacity, which study distributed transmission in different scenarios from a transmission-capacity perspective. Transmission capacity is spatial throughput metric in a large-scale wireless network with outage constraints. To understand the fundamental limits of distributed transmission, these three directions are investigated from the underlying tradeoffs in different transmission scenarios. All analytic results regarding the three directions are rigorously derived and proved under the framework of transmission capacity. For the first direction, three distributed opportunistic scheduling schemes -- distributed channel-aware, interferer-aware and interferer-channel-aware scheduling are proposed. The main idea of the three schemes is to avoid transmitting in a deep fading and/or sever interfering context. Theoretical analysis and simulations show that the three schemes are able to achieve high transmission capacity and reliability. The second direction focuses on the study of the transmission capacity problem in a distributed multicast transmission scenario. Multicast transmission, wherein the same packet must be delivered to multiple receivers, has several distinctive traits as opposed to more commonly studied unicast transmission. The general expression for the scaling law of multicast transmission capacity is found and it can provide some insight on how to do distributed single-hop and multi-hop retransmissions. In the third direction, the transmission capacity problem is investigated for Markovain fading channels with temporal and spatial ergodicity. The scaling law of the ergodic transmission capacity is derived and it can indicate a long-term distributed transmission and interference management policy for enhancing transmission capacity. / text

As the trends towards decentralization, miniaturization, and longevity of deployment continue in many domains, power management has become increasingly important. In this work, we develop power-aware control strategies for wireless sensor networks to improve the lifetime of the network and to ensure that the desired performance is guaranteed. For the case of static networks (networks of agents with no mobility), we identify the problem of the effects of power variations on the performance of an individual sensing device and on the entire network. To address this problem in a randomly deployed sensor network comprising of sensing devices whose sensing range is a function of transmitted power, we propose power-aware controllers to compensate for the variations in available power and maintain desired performance. We also propose a novel energy-efficient sleep-scheduling scheme that is random in nature and allows limited coordination among neighboring sensors for making switching decisions. This scheme is based on the concept of a hard-core point process from stochastic geometry, in which neighboring points are allowed to interact with each other through some predefined interaction laws. For the case of mobile networks (networks of agents with mobility), we propose a solid framework for distributed power-aware mobility strategies that can achieve any desired global objective while minimizing total energy consumption. This goal is achieved by first exploring fundamental trade-offs among various modes of operations of mobile devices and then exploiting these trade-offs for minimizing energy consumption. Through this framework, a whole class of decentralized power-aware controllers emerge for solving canonical problems in multi-agent systems like connectivity maintenance, rendezvous, and coverage control.

Dans cette thèse, nous analysons les performances des réseaux de communication à l'aide d’approches issues de la théorie des jeux. Cette thèse se présente en deux parties. La première partie étudie la performance des réseaux ad-hoc, cellulaires et de transport en tenant compte d’effets spatiaux. La deuxième partie adresse des problématiques économiques dans les réseaux de communications, liées à la réglementation de la «neutralité du réseau». Ici, nous étudions la concurrence des prix ainsi que des mécanismes de partage des revenus entre fournisseurs de services réseau.Dans la première partie, nous utilisons des modèles de jeu d’accès canal (MAC) et jeu de brouillage pour étudier les performances d'un réseau mobile ad hoc (MANET), et de jeux de routage afin d'étudier les performances d'un réseau de transport. Dans les réseaux cellulaires, nous étudions l'effet de la réduction de la densité spatiale des stations de base sur la quantité de rayonnement au corps humain (réseau vert).Les considérations géométriques jouent un rôle important dans les performances des réseaux sans fils. Par exemple, la position des nœuds affecte le niveau des interférences. Dans les MANETS, la mobilité des nœuds conduit à une observation différente du niveau d’interférences provenant de leurs voisins, et aussi due à la nature décentralisée du réseau, les utilisateurs peuvent adopter un comportement égoïste dans le partage des ressources. Afin de modéliser les propriétés géométriques du réseau ainsi que le comportement égoïste des utilisateurs, nous utilisons la géométrie stochastique et la théorie des jeux. Notre travail a développé un mécanisme de tarification et a montré qu’en définissant un prix approprié, tous les utilisateurs pouvaient être amenés à recevoir une part équitable des ressources conduisant à un optimal global des performances du réseau. Nous considérons aussi une configuration antagoniste où certain nœuds tendent à dégrader les performances du réseau en brouillant les communications des autres nœuds du réseau. Dans la deuxième partie de la thèse, nous étudions des aspects économiques dans les réseaux communication. Les représentants de plusieurs fournisseurs d'accès Internet (ISP) ont exprimé leur souhait de voir un changement important dans les politiques de tarification de l'Internet. En particulier, ils aimeraient voir les fournisseurs de contenu (CP) payer pour l'utilisation du réseau, compte tenu de la grande quantité de ressources qu'ils utilisent. Ce qui serait une violation flagrante du «principe de neutralité des réseaux» qui a caractérisé le développement de l'Internet filaire. La thèse a étudiée la possibilité de l’introduction d’un régulateur facilitant les interactions monétaires entre les ISP et les CP dans un régime non neutre. En utilisant des outils issus de la théorie des jeux et de la conception de mécanismes, nous avons développé deux mécanismes de négociation décidant des paiements entre les ISPs et CPs. Nous montrons que si les joueurs négocient avant de fixer les prix d’accès des utilisateurs finaux, ceci conduit à un équilibre favorable où tous les joueurs ressortent gagnant. Nous considérons également le cas où certains CPs établissent des contrats d’exclusivités avec les ISP afin d’obtenir des traitements préférentiels et en étudions l’impact sur les fournisseurs d’accès et les utilisateurs finaux. Avec la croissance du commerce de l’internet, la régulation des interactions monétaires entre différents fournisseurs de services est inévitable. Notre travail fournit des lignes directrices importantes sur la façon dont l'Internet doit être réglementé de telle sorte que les intérêts des utilisateurs finaux sont protégés / In this thesis we analyze the performance of communication networks using game theoretic approaches. The thesis is in two parts. The first part studies the performance of Ad hoc, cellular and transportation networks taking into consideration spatial effects. The second part studies economic issues in the communication networks related to the `net neutrality' regulations. Here we study price competition and revenue sharing mechanisms between the network service providers.In the first part, we use Medium Access Control (MAC) game and Jamming game models to study the performance of a Mobile Ad hoc NETwork (MANET), and routing games to study the performance of a transportation network. In the cellular networks, we study the effect of reducing the spatial density of base stations on the amount of radiation to human body (green networking). Geometric aspects play an important role in the performance of wireless networks. For example, node locations affect the amount of interference. In MANETs, the mobility results in users experiencing different amount of interference from their neighbors, and also due to decentralized nature of the network the users can be selfish in sharing the resources. To model the geometrical properties of the network and selfish behavior of the users we used stochastic geometry and game theory. Our work developed a pricing mechanism and showed that with an `appropriate' price all the users can be made to get a fair share of the resources resulting in global optimal network performance. We also considered an adversarial setting where some of the nodes aim to degrade the performance of the network by jamming other nodes’ transmissions.In the second part of the thesis, we study economics aspects in communication networks. Representatives of several Internet access providers (ISPs) have expressed their wish to see a substantial change in the Internet pricing policies. In particular, they would like to see content providers (CPs) pay for use of the network, given the large amount of resources they use. This would be in clear violation of the ``net neutrality'' principle that had characterized the development of the wireline Internet. The thesis explored possibility of a regulator facilitating monetary interactions between the ISPs and CPs in a nonneutral regime. Using tools from game theory and mechanism design we developed two bargaining mechanisms to decide payments between the ISPs and CPs. We showed that if the players bargain before they set the access prices for end users, it results in a favorable equilibrium where every player benefits. We also considered the case where some of CPs make exclusive contracts with the ISPs to get preferential treatment and studied its impact on both the service providers and the end users.As the Internet commerce grows, regulation of the monetary interaction between various service providers is unavoidable. Our work provides important policy guidelines on how the Internet should be regulated such that the end users' interests are protected

Orientador: Pedro Jose Catuogno / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-13T12:34:53Z (GMT). No. of bitstreams: 1 Felix_LucianoVianna_M.pdf: 566321 bytes, checksum: f717034fada0c65f1b886ba7bd821902 (MD5) Previous issue date: 2009 / Resumo: Neste trabalho estudamos a geometria dos caminhos em grupos de Lie usando a exponencial estocástica e o logaritmo estocástico. Apresentamos as construções geométricas do espaço tangente, uma métrica e uma conexão natural as caminhos em grupos de Lie. Finalmente apresentamos uma situação em que essa conexão é Levi-Civita e outra que não é / Abstract: In this work, we study the path geometry in Lie groups using the stochastic exponential and the stochastic logarithm. We show the geometric constructions of tangent space, one metric and one natural conection of Lie groups valued path. Finelly we show one situation that this conection is Levi-Civita and another one that is not / Mestrado / Geometria / Mestre em Matemática

Orientador: Paulo Regis Caron Ruffino / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-13T23:01:19Z (GMT). No. of bitstreams: 1 Costa_PauloHenriquePereirada_M.pdf: 875708 bytes, checksum: 8862a1813f1bb85b5d0269462a80501e (MD5) Previous issue date: 2009 / Resumo: O objetivo desse trabalho é estudar as equações de Hamilton no contexto estocástico. Sendo necessário para tal um pouco de conhecimento a cerca dos seguintes assuntos: cálculo estocástico, geometria de segunda ordem, estruturas simpléticas e de Poisson. Abordamos importantes resultados, dentre eles o teorema de Darboux (coordenadas locais) em variedades simpléticas, teorema de Lie-Weinstein que de certa forma generaliza o teorema de Darboux em variedades de Poisson. Veremos que apesar de o ambiente natural para se estudar sistemas hamiltonianos ser variedades simpléticas, no caso estocástico esses sistemas se adaptam bem em variedades de Poisson. Além disso, para atingir a nossa meta, estudaremos equações diferenciais estocásticas em variedades de dimensão finita usando o operador de Stratonovich / Abstract: This dissertation deals with transfering Hamilton's equations in stochastic context. This requires some knowledge about the following: stochastic calculus, second order geometry and Poisson and simplectic structures. Important results that will be discussed in this theory are Darboux's theorem (local coordinates) for simplectic manifolds, and Lie-Weintein's theorem that is in a certain way of Darboux's theorem on Poisson manifolds. We will see that although the natural environment for studying hamiltonian systems is symplectic manifolds, if we have a Poisson structure we will still be able to study them. Moreover, to achieve our goal, we will study stochastic differential equations on finite dimensional manifolds using the Stratonovich operator / Mestrado / Geometria Estocastica / Mestre em Matemática