Context-based wireless mesh networks

In the modern society, new devices, applications and technologies, with sophisticated capabilities, are converging in the same network infrastructure. Users are also increasingly demanding in personal preferences and expectations, desiring Internet connectivity anytime and everywhere. These aspects have triggered many research efforts, since the current Internet is reaching a breaking point trying to provide enough flexibility for users and profits for operators, while dealing with the complex requirements raised by the recent evolution. Fully aligned with the future Internet research, many solutions have been proposed to enhance the current Internet-based architectures and protocols, in order to become context-aware, that is, to be dynamically adapted to the change of the information characterizing any network entity. In this sense, the presented Thesis proposes a new architecture that allows to create several networks with different characteristics according to their context, on the top of a single Wireless Mesh Network (WMN), which infrastructure and protocols are very flexible and self-adaptable. More specifically, this Thesis models the context of users, which can span from their security, cost and mobility preferences, devices’ capabilities or services’ quality requirements, in order to turn a WMN into a set of logical networks. Each logical network is configured to meet a set of user context needs (for instance, support of high mobility and low security). To implement this user-centric architecture, this Thesis uses the network virtualization, which has often been advocated as a mean to deploy independent network architectures and services towards the future Internet, while allowing a dynamic resource management. This way, network virtualization can allow a flexible and programmable configuration of a WMN, in order to be shared by multiple logical networks (or virtual networks - VNs). Moreover, the high level of isolation introduced by network virtualization can be used to differentiate the protocols and mechanisms of each context-aware VN. This architecture raises several challenges to control and manage the VNs on-demand, in response to user and WMN dynamics. In this context, we target the mechanisms to: (i) discover and select the VN to assign to an user; (ii) create, adapt and remove the VN topologies and routes. We also explore how the rate of variation of the user context requirements can be considered to improve the performance and reduce the complexity of the VN control and management. Finally, due to the scalability limitations of centralized control solutions, we propose a mechanism to distribute the control functionalities along the architectural entities, which can cooperate to control and manage the VNs in a distributed way.

Mining biomedical information from scientific literature

The rapid evolution and proliferation of a world-wide computerized network, the Internet, resulted in an overwhelming and constantly growing amount of publicly available data and information, a fact that was also verified in biomedicine. However, the lack of structure of textual data inhibits its direct processing by computational solutions. Information extraction is the task of text mining that intends to automatically collect information from unstructured text data sources. The goal of the work described in this thesis was to build innovative solutions for biomedical information extraction from scientific literature, through the development of simple software artifacts for developers and biocurators, delivering more accurate, usable and faster results. We started by tackling named entity recognition - a crucial initial task - with the development of Gimli, a machine-learning-based solution that follows an incremental approach to optimize extracted linguistic characteristics for each concept type. Afterwards, Totum was built to harmonize concept names provided by heterogeneous systems, delivering a robust solution with improved performance results. Such approach takes advantage of heterogenous corpora to deliver cross-corpus harmonization that is not constrained to specific characteristics. Since previous solutions do not provide links to knowledge bases, Neji was built to streamline the development of complex and custom solutions for biomedical concept name recognition and normalization. This was achieved through a modular and flexible framework focused on speed and performance, integrating a large amount of processing modules optimized for the biomedical domain. To offer on-demand heterogenous biomedical concept identification, we developed BeCAS, a web application, service and widget. We also tackled relation mining by developing TrigNER, a machine-learning-based solution for biomedical event trigger recognition, which applies an automatic algorithm to obtain the best linguistic features and model parameters for each event type. Finally, in order to assist biocurators, Egas was developed to support rapid, interactive and real-time collaborative curation of biomedical documents, through manual and automatic in-line annotation of concepts and relations. Overall, the research work presented in this thesis contributed to a more accurate update of current biomedical knowledge bases, towards improved hypothesis generation and knowledge discovery.

Network virtualisation from an operator perspective

Network virtualisation is seen as a promising approach to overcome the so-called “Internet impasse” and bring innovation back into the Internet, by allowing easier migration towards novel networking approaches as well as the coexistence of complementary network architectures on a shared infrastructure in a commercial context. Recently, the interest from the operators and mainstream industry in network virtualisation has grown quite significantly, as the potential benefits of virtualisation became clearer, both from an economical and an operational point of view. In the beginning, the concept has been mainly a research topic and has been materialized in small-scale testbeds and research network environments. This PhD Thesis aims to provide the network operator with a set of mechanisms and algorithms capable of managing and controlling virtual networks. To this end, we propose a framework that aims to allocate, monitor and control virtual resources in a centralized and efficient manner. In order to analyse the performance of the framework, we performed the implementation and evaluation on a small-scale testbed. To enable the operator to make an efficient allocation, in real-time, and on-demand, of virtual networks onto the substrate network, it is proposed a heuristic algorithm to perform the virtual network mapping. For the network operator to obtain the highest profit of the physical network, it is also proposed a mathematical formulation that aims to maximize the number of allocated virtual networks onto the physical network. Since the power consumption of the physical network is very significant in the operating costs, it is important to make the allocation of virtual networks in fewer physical resources and onto physical resources already active. To address this challenge, we propose a mathematical formulation that aims to minimize the energy consumption of the physical network without affecting the efficiency of the allocation of virtual networks. To minimize fragmentation of the physical network while increasing the revenue of the operator, it is extended the initial formulation to contemplate the re-optimization of previously mapped virtual networks, so that the operator has a better use of its physical infrastructure. It is also necessary to address the migration of virtual networks, either for reasons of load balancing or for reasons of imminent failure of physical resources, without affecting the proper functioning of the virtual network. To this end, we propose a method based on cloning techniques to perform the migration of virtual networks across the physical infrastructure, transparently, and without affecting the virtual network. In order to assess the resilience of virtual networks to physical network failures, while obtaining the optimal solution for the migration of virtual networks in case of imminent failure of physical resources, the mathematical formulation is extended to minimize the number of nodes migrated and the relocation of virtual links. In comparison with our optimization proposals, we found out that existing heuristics for mapping virtual networks have a poor performance. We also found that it is possible to minimize the energy consumption without penalizing the efficient allocation. By applying the re-optimization on the virtual networks, it has been shown that it is possible to obtain more free resources as well as having the physical resources better balanced. Finally, it was shown that virtual networks are quite resilient to failures on the physical network.