Communication between nodes for autonomic and distributed management

Over the last decade, the most widespread approaches for traditional management were based on the Simple Network Management Protocol (SNMP) or Common Management Information Protocol (CMIP). However, they both have several problems in terms of scalability, due to their centralization characteristics. Although the distributed management approaches exhibit better performance in terms of scalability, they still underperform regarding communication costs, autonomy, extensibility, exibility, robustness, and cooperation between network nodes. The cooperation between network nodes normally requires excessive overheads for synchronization and dissemination of management information in the network. For emerging dynamic and large-scale networking environments, as envisioned in Next Generation Networks (NGNs), exponential growth in the number of network devices and mobile communications and application demands is expected. Thus, a high degree of management automation is an important requirement, along with new mechanisms that promote it optimally and e ciently, taking into account the need for high cooperation between the nodes. Current approaches for self and autonomic management allow the network administrator to manage large areas, performing fast reaction and e ciently facing unexpected problems. The management functionalities should be delegated to a self-organized plane operating within the network, that decrease the network complexity and the control information ow, as opposed to centralized or external servers. This Thesis aims to propose and develop a communication framework for distributed network management which integrates a set of mechanisms for initial communication, exchange of management information, network (re) organization and data dissemination, attempting to meet the autonomic and distributed management requirements posed by NGNs. The mechanisms are lightweight and portable, and they can operate in di erent hardware architectures and include all the requirements to maintain the basis for an e cient communication between nodes in order to ensure autonomic network management. Moreover, those mechanisms were explored in diverse network conditions and events, such as device and link errors, di erent tra c/network loads and requirements. The results obtained through simulation and real experimentation show that the proposed mechanisms provide a lower convergence time, smaller overhead impact in the network, faster dissemination of management information, increase stability and quality of the nodes associations, and enable the support for e cient data information delivery in comparison to the base mechanisms analyzed. Finally, all mechanisms for communication between nodes proposed in this Thesis, that support and distribute the management information and network control functionalities, were devised and developed to operate in completely decentralized scenarios.

Management and Control of Water Supply Systems

The fast increase in the energy’s price has brought a growing concern about the highly expensive task of transporting water. By creating an hydraulic model of the Water Supply System’s (WSS) network and predicting its behaviour, it is possible to take advantage of the energy’s tariffs, reducing the total cost on pumping activities. This thesis was developed, in association with a technology transfer project called the E-Pumping. It focuses on finding a flexible supervision and control strategy, adaptable to any existent Water Supply System (WSS), as well as forecasting the water demand on a time period chosen by the end user, so that the pumping actions could be planned to an optimum schedule, that minimizes the total operational cost. The OPC protocol, associated to a MySQL database were used to develop a flexible tool of supervision and control, due to their adaptability to function with equipments from various manufacturers, being another integrated modular part of the E-Pumping project. Furthermore, in this thesis, through the study and performance tests of several statistical models based on time series, specifically applied to this problem, a forecasting tool adaptable to any station, and whose model parameters are automatically refreshed at runtime, was developed and added to the project as another module. Both the aforementioned modules were later integrated with an Graphical User Interface (GUI) and installed in a pilot application at the ADDP’s network. The implementation of this software on WSSs across the country will reduce the water supply companies’ running costs, improving their market competition and, ultimately, lowering the water price to the end costumer.

Environmental factors, clipping and fire: effects on cerrado (Brazilian savanna) native and invasive grasses

The Brazilian Cerrado houses a hugely diverse biota and is considered a conservation hotspot. One of the greatest threats to the integrity of this ecosystem is introduced African grasses, which can competitively exclude native grasses and cause changes in the microclimate and other disturbances. The Cerrado is a mosaic vegetation that provides different combinations, both spatially and temporally, of conditions that can become natural stressors to the herbaceous vegetation (water, nutrient and light availability). These mosaics are reflected in differences in relationships among native and invasive species, affecting competition and creating situations (place/season) that are more, or less, susceptible to invasion. The present study aimed to identify the different biological responses of native (Aristida recurvata, Aristida setifolia, Axonopus barbigerus, Echinolaena inflexa, Gymnopogon spicatus, Paspalum gardnerianum, Paspalum stellatum, Schizachyrium microstachyum, Schizachyrium sanguineum) and invasive (Melinis minutiflora and Andropogon gayanus) grasses to variations in natural stressors and to disturbance (fire and clipping), in order to understand changes in ecosystem functioning and competition processes between the grasses, and to understand invasion dynamics in this ecosystem. The presence of invasive species proved to affect the ecosystem functioning by increasing soil feeding activity. These differences were no longer observed in the dry season or when fires were frequent, showing that water availability and fire are more detrimental to soil feeding activity than is the vegetation. Laboratory experiments showed that both drought and flood simulated scenarios damaged both species, although the invasive species performed better under all watering conditions and responded better to fertilization. Underlying mechanisms such as the efficiency of photosynthesis and antioxidant mechanisms helped to explain this behavior. The invasive species grew faster and showed less cellular damage and a healthier photosystem, reflected in higher assimilation rates under stress. These differences between the native and invasive species were reduced with clipping, especially in dry soil with no fertilization, where the native species recovered better in relation to the pre-clipping levels. Flooding was as stressful as drought, but the invasive species can bypass this issue by growing an extensive root system, especially in the better-drained soils. Fire is more detrimental than clipping, with a slower recovery, while post-fire temperatures affect the germination of both invasive and native seeds and may be an important factor influencing the persistence of a diverse biota. This approach will finally contribute to the choice of the appropriate management techniques to preserve the Cerrado’s biodiversity.

Phase transitions and nonlinear phenomena in neuronal network models

Communication and cooperation between billions of neurons underlie the power of the brain. How do complex functions of the brain arise from its cellular constituents? How do groups of neurons self-organize into patterns of activity? These are crucial questions in neuroscience. In order to answer them, it is necessary to have solid theoretical understanding of how single neurons communicate at the microscopic level, and how cooperative activity emerges. In this thesis we aim to understand how complex collective phenomena can arise in a simple model of neuronal networks. We use a model with balanced excitation and inhibition and complex network architecture, and we develop analytical and numerical methods for describing its neuronal dynamics. We study how interaction between neurons generates various collective phenomena, such as spontaneous appearance of network oscillations and seizures, and early warnings of these transitions in neuronal networks. Within our model, we show that phase transitions separate various dynamical regimes, and we investigate the corresponding bifurcations and critical phenomena. It permits us to suggest a qualitative explanation of the Berger effect, and to investigate phenomena such as avalanches, band-pass filter, and stochastic resonance. The role of modular structure in the detection of weak signals is also discussed. Moreover, we find nonlinear excitations that can describe paroxysmal spikes observed in electroencephalograms from epileptic brains. It allows us to propose a method to predict epileptic seizures. Memory and learning are key functions of the brain. There are evidences that these processes result from dynamical changes in the structure of the brain. At the microscopic level, synaptic connections are plastic and are modified according to the dynamics of neurons. Thus, we generalize our cortical model to take into account synaptic plasticity and we show that the repertoire of dynamical regimes becomes richer. In particular, we find mixed-mode oscillations and a chaotic regime in neuronal network dynamics.