A Green Approach for Selfish Misbehavior Detection in 802.11-Based Wireless Networks

IEEE 802.11 is one of the most well-established and widely used standard for wireless LAN. Its Medium Access control (MAC) layer assumes that the devices adhere to the standard’s rules and timers to assure fair access and sharing of the medium. However, wireless cards driver flexibility and configurability make it possible for selfish misbehaving nodes to take advantages over the other well-behaving nodes. The existence of selfish nodes degrades the QoS for the other devices in the network and may increase their energy consumption. In this paper we propose a green solution for selfish misbehavior detection in IEEE 802.11-based wireless networks. The proposed scheme works in two phases: Global phase which detects whether the network contains selfish nodes or not, and Local phase which identifies which node or nodes within the network are selfish. Usually, the network must be frequently examined for selfish nodes during its operation since any node may act selfishly. Our solution is green in the sense that it saves the network resources as it avoids wasting the nodes energy by examining all the individual nodes of being selfish when it is not necessary. The proposed detection algorithm is evaluated using extensive OPNET simulations. The results show that the Global network metric clearly indicates the existence of a selfish node while the Local nodes metric successfully identified the selfish node(s). We also provide mathematical analysis for the selfish misbehaving and derived formulas for the successful channel access probability.

Sensor Integration for Smart Cities Using Multi-Hop Networks

Smart Cities are designed to be living systems and turn urban dwellers life more comfortable and interactive by keeping them aware of what surrounds them, while leaving a greener footprint. The Future Cities Project [1] aims to create infrastructures for research in smart cities including a vehicular network, the BusNet, and an environmental sensor platform, the Urban Sense. Vehicles within the BusNet are equipped with On Board Units (OBUs) that offer free Wi-Fi to passengers and devices near the street. The Urban Sense platform is composed by a set of Data Collection Units (DCUs) that include a set of sensors measuring environmental parameters such as air pollution, meteorology and noise. The Urban Sense platform is expanding and receptive to add new sensors to the platform. The parnership with companies like TNL were made and the need to monitor garbage street containers emerged as air pollution prevention. If refuse collection companies know prior to the refuse collection which route is the best to collect the maximum amount of garbage with the shortest path, they can reduce costs and pollution levels are lower, leaving behind a greener footprint. This dissertation work arises in the need to monitor the garbage street containers and integrate these sensors into an Urban Sense DCU. Due to the remote locations of the garbage street containers, a network extension to the vehicular network had to be created. This dissertation work also focus on the Multi-hop network designed to extend the vehicular network coverage area to the remote garbage street containers. In locations where garbage street containers have access to the vehicular network, Roadside Units (RSUs) or Access Points (APs), the Multi-hop network serves has a redundant path to send the data collected from DCUs to the Urban Sense cloud database. To plan this highly dynamic network, the Wi-Fi Planner Tool was developed. This tool allowed taking measurements on the field that led to an optimized location of the Multi-hop network nodes with the use of radio propagation models. This tool also allowed rendering a temperature-map style overlay for Google Earth [2] application. For the DCU for garbage street containers the parner company provided the access to a HUB (device that communicates with the sensor inside the garbage containers). The Future Cities use the Raspberry pi as a platform for the DCUs. To collect the data from the HUB a RS485 to RS232 converter was used at the physical level and the Modbus protocol at the application level. To determine the location and status of the vehicles whinin the vehicular network a TCP Server was developed. This application was developed for the OBUs providing the vehicle Global Positioning System (GPS) location as well as information of when the vehicle is stopped, moving, on idle or even its slope. To implement the Multi-hop network on the field some scripts were developed such as pingLED and “shark”. These scripts helped upon node deployment on the field as well as to perform all the tests on the network. Two setups were implemented on the field, an urban setup was implemented for a Multi-hop network coverage survey and a sub-urban setup was implemented to test the Multi-hop network routing protocols, Optimized Link State Routing Protocol (OLSR) and Babel.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Optical measurements of rat muscle samples under treatment with ethylene glycol and glucose

With the objective to study the variation of optical properties of rat muscle during optical clearing, we have performed a set of optical measurements from that kind of tissue. The measurements performed were total transmittance, collimated transmittance, specular reflectance and total reflectance. This set of measurements is sufficient to determine diffuse reflectance and absorbance of the sample, also necessary to estimate the optical properties. All the performed measurements and calculated quantities will be used later in inverse Monte Carlo (IMC) simulations to determine the evolution of the optical properties of muscle during treatments with ethylene glycol and glucose. The results obtained with the measurements already provide some information about the optical clearing treatments applied to the muscle and translate the mechanisms of turning the tissue more transparent and sequence of regimes of optical clearing.

Software development for estimation of optical clearing agent’s diffusion coefficients in biological tissues

The study of chemical diffusion in biological tissues is a research field of high importance and with application in many clinical, research and industrial areas. The evaluation of diffusion and viscosity properties of chemicals in tissues is necessary to characterize treatments or inclusion of preservatives in tissues or organs for low temperature conservation. Recently, we have demonstrated experimentally that the diffusion properties and dynamic viscosity of sugars and alcohols can be evaluated from optical measurements. Our studies were performed in skeletal muscle, but our results have revealed that the same methodology can be used with other tissues and different chemicals. Considering the significant number of studies that can be made with this method, it becomes necessary to turn data processing and calculation easier. With this objective, we have developed a software application that integrates all processing and calculations, turning the researcher work easier and faster. Using the same experimental data that previously was used to estimate the diffusion and viscosity of glucose in skeletal muscle, we have repeated the calculations with the new application. Comparing between the results obtained with the new application and with previous independent routines we have demonstrated great similarity and consequently validated the application. This new tool is now available to be used in similar research to obtain the diffusion properties of other chemicals in different tissues or organs.

Three transducers for one photodetector: essays for optical communications

Dissertation presented to obtain the PhD degree in Electrical and Computer Engineering - Electronics

The Impact of Multifocal Intraocular Lens in Retinal Imaging with Optical Coherence Tomography

Multifocal intraocular lenses (MF IOLs) have concentric optical zones with different dioptric power, enabling patients to have good visual acuity at multiple focal points. However, several optical limitations have been attributed to this particular design. The purpose of this study is to access the effect of MF IOLs design on the accuracy of retinal optical coherence tomography (OCT). Cross-sectional study conducted at the Refractive Surgery Department of Central Lisbon Hospital Center. Twenty-three eyes of 15 patients with a diffractive MF IOL and 27 eyes of 15 patients with an aspheric monofocal IOL were included in this study. All patients underwent OCT macular scans using Heidelberg Spectralis®. Macular thickness and volume values and image quality (Q factor) were compared between the two groups. There were no statistically significant differences between both groups regarding macular thickness or volume measurements. Retinal OCT image quality was significantly lower in the MF IOL group (p < 0.01). MF IOLs are associated with a significant decrease in OCT image quality. However, this fact does not seem to compromise the accuracy of spectral domain OCT retinal measurements.

Social BPM – The role of social networks in business process management

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

MAC regenerative analysis of wireless Ad-Hoc networks

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Old cellulose for new multifunctional networks

Dissertação para obtenção do Grau de Doutor em Ciência e Engenharia de Materiais

Complex networks and data mining: toward a new perspective for the understanding of complex systems

Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.

Control in distribution networks with demand side management

The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

Electro-Optical/Infrared sensor turret integration on an aircraft - structural im-pact on LOCKHEED MARTIN C-130H and design methodology

The growing need to patrol and survey large maritime and terrestrial areas increased the need to integrate external sensors on aircraft in order to accomplish those patrols at increasingly higher altitudes, longer range and not depending upon vehicle type. The main focus of this work is to elaborate a practical, simple, effective and efficient methodology for the aircraft modification procedure resulting from the integration of an Elec-tro-Optical/Infra-Red (EO/IR) turret through a support structure. The importance of the devel-opment of a good methodology relies on the correct management of project variables as time, available resources and project complexity. The key is to deliver a proper tool for a project de-sign team that will be used to create a solution that fulfils all technical, non-technical and certi-fication requirements present in this field of transportation. The created methodology is inde-pendent of two main inputs: sensor model and aircraft model definition, and therefore it is in-tended to deliver the results for different projects besides the one that was presented in this work as a case study. This particular case study presents the development of a structure support for FLIR STAR SAPHIRE III turret integration on the front lower fuselage bulkhead (radome) of the LOCKHEED MARTIN C-130 H. Development of the case study focuses on the study of local structural analysis through the use of Finite Element Method (FEM). Development of this Dissertation resulted in a cooperation between Faculty of Science and Technology - Universidade Nova de Lisboa and the company OGMA - Indústria Aeronáutica de Portugal

A new credit monitoring framework for agents' networks

The purpose of this work is to develop a practicable approach for Telecom firms to manage the credit risk exposition to their commercial agents’ network. Particularly it will try to approach the problem of credit concession to clients’ from a corporation perspective and explore the particular scenario of agents that are part of the commercial chain of the corporation and therefore are not end-users. The agents’ network that served as a model for the presented study is composed by companies that, at the same time, are both clients and suppliers of the Telecommunication Company. In that sense the credit exposition analysis must took into consideration all financial fluxes, both inbound and outbound. The current strain on the Financial Sector in Portugal, and other peripheral European economies, combined with the high leverage situation of most companies, generates an environment prone to credit default risk. Due to these circumstances managing credit risk exposure is becoming increasingly a critical function for every company Financial Department. The approach designed in the current study combined two traditional risk monitoring tools: credit risk scoring and credit limitation policies. The objective was to design a new credit monitoring framework that is more flexible, uses both external and internal relationship history to assess risk and takes into consideration commercial objectives inside the agents’ network. Although not explored at length, the blueprint of a Credit Governance model was created for implementing the new credit monitoring framework inside the telecom firm. The Telecom Company that served as a model for the present work decided to implement the new Credit Monitoring framework after this was presented to its Executive Commission.

Reconstructing transcriptional regulatory networks using data integration and text mining

Transcriptional Regulatory Networks (TRNs) are powerful tool for representing several interactions that occur within a cell. Recent studies have provided information to help researchers in the tasks of building and understanding these networks. One of the major sources of information to build TRNs is biomedical literature. However, due to the rapidly increasing number of scientific papers, it is quite difficult to analyse the large amount of papers that have been published about this subject. This fact has heightened the importance of Biomedical Text Mining approaches in this task. Also, owing to the lack of adequate standards, as the number of databases increases, several inconsistencies concerning gene and protein names and identifiers are common. In this work, we developed an integrated approach for the reconstruction of TRNs that retrieve the relevant information from important biological databases and insert it into a unique repository, named KREN. Also, we applied text mining techniques over this integrated repository to build TRNs. However, was necessary to create a dictionary of names and synonyms associated with these entities and also develop an approach that retrieves all the abstracts from the related scientific papers stored on PubMed, in order to create a corpora of data about genes. Furthermore, these tasks were integrated into @Note, a software system that allows to use some methods from the Biomedical Text Mining field, including an algorithms for Named Entity Recognition (NER), extraction of all relevant terms from publication abstracts, extraction relationships between biological entities (genes, proteins and transcription factors). And finally, extended this tool to allow the reconstruction Transcriptional Regulatory Networks through using scientific literature.