Interacting agents on complex networks and stochastic processes in them

Nas últimas décadas, um grande número de processos têm sido descritos em termos de redes complexas. A teoria de redes complexas vem sendo utilizada com sucesso para descrever, modelar e caracterizar sistemas naturais, artificias e sociais, tais como ecossistemas, interações entre proteínas, a Internet, WWW, até mesmo as relações interpessoais na sociedade. Nesta tese de doutoramento apresentamos alguns modelos de agentes interagentes em redes complexas. Inicialmente, apresentamos uma breve introdução histórica (Capítulo 1), seguida de algumas noções básicas sobre redes complexas (Capítulo 2) e de alguns trabalhos e modelos mais relevantes a esta tese de doutoramento (Capítulo 3). Apresentamos, no Capítulo 4, o estudo de um modelo de dinâmica de opiniões, onde busca-se o consenso entre os agentes em uma população, seguido do estudo da evolução de agentes interagentes em um processo de ramificação espacialmente definido (Capítulo 5). No Capítulo 6 apresentamos um modelo de otimização de fluxos em rede e um estudo do surgimento de redes livres de escala a partir de um processo de otimização . Finalmente, no Capítulo 7, apresentamos nossas conclusões e perspectivas futuras.

Seamless integration of heterogeneous networks in multicast environments

Nowadays, communication environments are already characterized by a myriad of competing and complementary technologies that aim to provide an ubiquitous connectivity service. Next Generation Networks need to hide this heterogeneity by providing a new abstraction level, while simultaneously be aware of the underlying technologies to deliver richer service experiences to the end-user. Moreover, the increasing interest for group-based multimedia services followed by their ever growing resource demands and network dynamics, has been boosting the research towards more scalable and exible network control approaches. The work developed in this Thesis enables such abstraction and exploits the prevailing heterogeneity in favor of a context-aware network management and adaptation. In this scope, we introduce a novel hierarchical control framework with self-management capabilities that enables the concept of Abstract Multiparty Trees (AMTs) to ease the control of multiparty content distribution throughout heterogeneous networks. A thorough evaluation of the proposed multiparty transport control framework was performed in the scope of this Thesis, assessing its bene ts in terms of network selection, delivery tree recon guration and resource savings. Moreover, we developed an analytical study to highlight the scalability of the AMT concept as well as its exibility in large scale networks and group sizes. To prove the feasibility and easy deployment characteristic of the proposed control framework, we implemented a proof-of-concept demonstrator that comprehends the main control procedures conceptually introduced. Its outcomes highlight a good performance of the multiparty content distribution tree control, including its local and global recon guration. In order to endow the AMT concept with the ability to guarantee the best service experience by the end-user, we integrate in the control framework two additional QoE enhancement approaches. The rst employs the concept of Network Coding to improve the robustness of the multiparty content delivery, aiming at mitigating the impact of possible packet losses in the end-user service perception. The second approach relies on a machine learning scheme to autonomously determine at each node the expected QoE towards a certain destination. This knowledge is then used by di erent QoE-aware network management schemes that, jointly, maximize the overall users' QoE. The performance and scalability of the control procedures developed, aided by the context and QoE-aware mechanisms, show the advantages of the AMT concept and the proposed hierarchical control strategy for the multiparty content distribution with enhanced service experience. Moreover we also prove the feasibility of the solution in a practical environment, and provide future research directions that bene t the evolved control framework and make it commercially feasible.

Monitoring and all-optical signal processing techniques for transparent networks

Optical networks are under constant evolution. The growing demand for dynamism require devices that can accommodate different types of traffic. Thus the study of transparent optical networks arises. This approach makes optical networks more "elegant" , due to a more efficient use of network resources. In this thesis, the author proposes devices that intend to form alternative approaches both in the state of art of these same technologies both in the fitting of this technologies in transparent optical networks. Given that full transparency is difficult to achieve with current technology (perhaps with more developed optical computing this is possible), the author proposes techniques with different levels of transparency. On the topic of performance of optical networks, the author proposes two techniques for monitoring chromatic dispersion with different levels of transparency. In Chapter 3 the proposed technique seems to make more sense for long-haul optical transmission links and high transmission rates, not only due to its moderate complexity but also to its potential moderate/high cost. However it is proposed to several modulation formats, particularly those that have a protruding clock component. In Chapter 4 the transparency level was not tested for various modulation formats, however some transparency is achieved by not adding any electrical device after the receiver (other than an analog-digital converter). This allows that this technique can operate at high transmission rates in excess of 100 Gbit / s, if electro-optical asynchronous sampling is used before the optical receiver. Thus a low cost and low bandwidth photo-detector can be used. In chapter 5 is demonstrated a technique for simultaneously monitoring multiple impairments of the optical network by generating novel performance analysis diagrams and by use of artificial neural networks. In chapter 6 the author demonstrates an all-optical technique for controlling the optical state of polarization and an example of how all-optical signal processing can fully cooperate with optical performance monitoring.

Forwarding and security in vehicular networks

The growing research in vehicular network solutions provided the rise of interaction in these highly dynamic environments in the market. The developed architectures do not usually focus, however, in security aspects. Common security strategies designed for the Internet require IP. Since nodes' addresses in a vehicular network are too dynamic, such solutions would require cumbersome negotiations, which would make them unsuitable to these environments. The objective of this dissertation is to develop, and test a scalable, lightweight, layer 3 security protocol for vehicular networks, in which nodes of the network are able to set up long-term security associations with a Home Network, avoiding session renegotiations due to lack of connectivity and reduce the protocol stacking. This protocol allows to provide security independent of the nodes (vehicles) position, of its addressing and of the established path to access the Internet, allowing the mobility of vehicles and of its active sessions seamlessly without communication failures.

On the application of contextual IoT service discovery in Information Centric Networks

The continuous flow of technological developments in communications and electronic industries has led to the growing expansion of the Internet of Things (IoT). By leveraging the capabilities of smart networked devices and integrating them into existing industrial, leisure and communication applications, the IoT is expected to positively impact both economy and society, reducing the gap between the physical and digital worlds. Therefore, several efforts have been dedicated to the development of networking solutions addressing the diversity of challenges associated with such a vision. In this context, the integration of Information Centric Networking (ICN) concepts into the core of IoT is a research area gaining momentum and involving both research and industry actors. The massive amount of heterogeneous devices, as well as the data they produce, is a significant challenge for a wide-scale adoption of the IoT. In this paper we propose a service discovery mechanism, based on Named Data Networking (NDN), that leverages the use of a semantic matching mechanism for achieving a flexible discovery process. The development of appropriate service discovery mechanisms enriched with semantic capabilities for understanding and processing context information is a key feature for turning raw data into useful knowledge and ensuring the interoperability among different devices and applications. We assessed the performance of our solution through the implementation and deployment of a proof-of-concept prototype. Obtained results illustrate the potential of integrating semantic and ICN mechanisms to enable a flexible service discovery in IoT scenarios.