A module for the FTT-SE protocol in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.

TEC4SEA - A Modular Platform for Research, Test and Validation of Technologies Supporting a Sustainable Blue Economy

This paper presents the TEC4SEA research infrastructure created in Portugal to support research, development, and validation of marine technologies. It is a multidisciplinary open platform, capable of supporting research, development, and test of marine robotics, telecommunications, and sensing technologies for monitoring and operating in the ocean environment. Due to the installed research facilities and its privileged geographic location, it allows fast access to deep sea, and can support multidisciplinary research, enabling full validation and evaluation of technological solutions designed for the ocean environment. It is a vertically integrated infrastructure, in the sense that it possesses a set of skills and resources which range from pure conceptual research to field deployment missions, with strong industrial and logistic capacities in the middle tier of prototype production. TEC4SEA is open to the entire scientific and enterprise community, with a free access policy for researchers affiliated with the research units that ensure its maintenance and sustainability. The paper describes the infrastructure in detail, and discusses associated research programs, providing a strategic vision for deep sea research initiatives, within the context of both the Portuguese National Ocean Strategy and European Strategy frameworks.

An Exact Schedulability Test for Global FP Using State Space Pruning

Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

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.

mRPL: Boosting mobility in the Internet of Things

The 6loWPAN (the light version of IPv6) and RPL (routing protocol for low-power and lossy links) protocols have become de facto standards for the Internet of Things (IoT). In this paper, we show that the two native algorithms that handle changes in network topology – the Trickle and Neighbor Discovery algorithms – behave in a reactive fashion and thus are not prepared for the dynamics inherent to nodes mobility. Many emerging and upcoming IoT application scenarios are expected to impose real-time and reliable mobile data collection, which are not compatible with the long message latency, high packet loss and high overhead exhibited by the native RPL/6loWPAN protocols. To solve this problem, we integrate a proactive hand-off mechanism (dubbed smart-HOP) within RPL, which is very simple, effective and backward compatible with the standard protocol. We show that this add-on halves the packet loss and reduces the hand-off delay dramatically to one tenth of a second, upon nodes’ mobility, with a sub-percent overhead. The smart-HOP algorithm has been implemented and integrated in the Contiki 6LoWPAN/RPL stack (source-code available on-line mrpl: smart-hop within rpl, 2014) and validated through extensive simulation and experimentation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Experimental characterization of the out-of-plane performance of regular stone masonry walls, including test setups and axial load influence

Stone masonry is one of the oldest and most worldwide used building techniques. Nevertheless, the structural response of masonry structures is complex and the effective knowledge about their mechanical behaviour is still limited. This fact is particularly notorious when dealing with the description of their out-of-plane behaviour under horizontal loadings, as is the case of the earthquake action. In this context, this paper describes an experimental program, conducted in laboratory environment, aiming at characterizing the out-of-plane behaviour of traditional unreinforced stone masonry walls. In the scope of this campaign, six full-scale sacco stone masonry specimens were fully characterised regarding their most important mechanic, geometric and dynamic features and were tested resorting to two different loading techniques under three distinct vertical pre-compression states; three of the specimens were subjected to an out-of-plane surface load by means of a system of airbags and the remaining were subjected to an out-of-plane horizontal line-load at the top. From the experiments it was possible to observe that both test setups were able to globally mobilize the out-of-plane response of the walls, which presented substantial displacement capacity, with ratios of ultimate displacement to the wall thickness ranging between 26 and 45 %, as well as good energy dissipation capacity. Finally, very interesting results were also obtained from a simple analytical model used herein to compute a set of experimental-based ratios, namely between the maximum stability displacement and the wall thickness for which a mean value of about 60 % was found.

Adaptação Cultural e Linguística do Trunk Control Test: avaliação das propriedades psicométricas

Introdução: O controlo postural do tronco é um fator preditivo de autonomia, sendo fundamental a existência de instrumentos válidos e fiáveis a fim da sua avaliação na população portuguesa. Objetivo: Traduzir e adaptar o Trunk Control Test (TCT) para a população portuguesa em indivíduos após AVE e avaliar as suas propriedades psicométricas. Métodos: O TCT foi sujeito aos processos de tradução e retroversão para a população portuguesa por dois tradutores bilingues e realizadas duas reuniões com painel de peritos na área. Avaliou-se a validade, a fiabilidade, a sensibilidade, a especificidade e o poder de resposta em 19 indivíduos com AVE. Para avaliar a validade de critério os indivíduos foram adicionalmente submetidos à Escala de Equilíbrio de Berg (EEB), à Avaliação Motora de Rivermead (AMR) e à Escala de Comprometimento do Tronco (ECT). A fiabilidade inter-observadores foi garantida por uma segunda amostra de 25 fisioterapeutas, através da avaliação do desempenho de um participante no TCT. Os dados foram analisados no programa SPSS 22.0. Resultados: O TCT apresentou baixa consistência interna ( =0,523) e fiabilidade inter-observadores substancial (k=0,662). Obteve-se forte correlação do TCT com a ECT (r=0,885) e AMR (r=0,864), e correlação moderada com a EEB (r=0,700). A validade de construção aponta para uma moderada correlação entre itens (KMO=0,755; Bartlett=0,001). Não foi possível obter os valores de sensibilidade, especificidade e poder de resposta do TCT. Conclusão: O estudo demonstrou que o TCT é um instrumento válido e fiável na avaliação da população portuguesa após AVE.

Amostragem Adaptativa em Redes de Sensores

Uma nova área tecnológica está em crescente desenvolvimento. Esta área, denominada de internet das coisas, surge na necessidade de interligar vários objetos para uma melhoria a nível de serviços ou necessidades por parte dos utilizadores. Esta dissertação concentra-se numa área específica da tecnologia internet das coisas que é a sensorização. Esta rede de sensorização é implementada pelo projeto europeu denominado de Future Cities [1] onde se cria uma infraestrutura de investigação e validação de projetos e serviços inteligentes na cidade do Porto. O trabalho realizado nesta dissertação insere-se numa das plataformas existentes nessa rede de sensorização: a plataforma de sensores ambientais intitulada de UrbanSense. Estes sensores ambientais que estão incorporados em Data Collect Unit (DCU), também denominados por nós, medem variáveis ambientais tais como a temperatura, humidade, ozono e monóxido de carbono. No entanto, os nós têm recursos limitados em termos de energia, processamento e memória. Apesar das grandes evoluções a nível de armazenamento e de processamento, a nível energético, nomeadamente nas baterias, não existe ainda uma evolução tão notável, limitando a sua operacionalidade [2]. Esta tese foca-se, essencialmente, na melhoria do desempenho energético da rede de sensores UrbanSense. A principal contribuição é uma adaptação do protocolo de redes Ad Hoc OLSR (Optimized Link State Routing Protocol) para ser usado por nós alimentados a energia renovável, de forma a aumentar a vida útil dos nós da rede de sensorização. Com esta contribuição é possível obter um maior número de dados durante períodos de tempo mais longos, aproximadamente 10 horas relativamente às 7 horas anteriores, resultando numa maior recolha e envio dos mesmos com uma taxa superior, cerca de 500 KB/s. Existindo deste modo uma aproximação analítica dos vários parâmetros existentes na rede de sensorização. Contudo, o aumento do tempo de vida útil dos nós sensores com recurso à energia renovável, nomeadamente, energia solar, incrementa o seu peso e tamanho que limita a sua mobilidade. Com o referido acréscimo a determinar e a limitar a sua mobilidade exigindo, por isso, um planeamento prévio da sua localização. Numa primeira fase do trabalho analisou-se o consumo da DCU, visto serem estes a base na infraestrutura e comunicando entre si por WiFi ou 3G. Após uma análise dos protocolos de routing com iv suporte para parametrização energética, a escolha recaiu sobre o protocolo OLSR devido à maturidade e compatibilidade com o sistema atual da DCU, pois apesar de existirem outros protocolos, a implementação dos mesmos, não se encontram disponível como software aberto. Para a validação do trabalho realizado na presente dissertação, é realizado um ensaio prévio sem a energia renovável, para permitir caracterização de limitações do sistema. Com este ensaio, tornou-se possível verificar a compatibilidade entre os vários materiais e ajustamento de estratégias. Num segundo teste de validação é concretizado um ensaio real do sistema com 4 nós a comunicar, usando o protocolo com eficiência energética. O protocolo é avaliado em termos de aumento do tempo de vida útil do nó e da taxa de transferência. O desenvolvimento da análise e da adaptação do protocolo de rede Ad Hoc oferece uma maior longevidade em termos de tempo de vida útil, comparando ao que existe durante o processamento de envio de dados. Apesar do tempo de longevidade ser inferior, quando o parâmetro energético se encontra por omissão com o fator 3, a realização da adaptação do sistema conforme a energia, oferece uma taxa de transferência maior num período mais longo. Este é um fator favorável para a abertura de novos serviços de envio de dados em tempo real ou envio de ficheiros com um tamanho mais elevado.