Cloud-assisted Wireless Body Area Networks

Wireless Body Area Networks (WBANs) have emerged as a promising technology for medical and non-medical applications. WBANs consist of a number of miniaturized, portable, and autonomous sensor nodes that are used for long-term health monitoring of patients. These sensor nodes continuously collect information of patients, which are used for ubiquitous health monitoring. In addition, WBANs may be used for managing catastrophic events and increasing the effectiveness and performance of rescue forces. The huge amount of data collected by WBAN nodes demands scalable, on-demand, powerful, and secure storage and processing infrastructure. Cloud computing is expected to play a significant role in achieving the aforementioned objectives. The cloud computing environment links different devices ranging from miniaturized sensor nodes to high-performance supercomputers for delivering people-centric and context-centric services to the individuals and industries. The possible integration of WBANs with cloud computing (WBAN-cloud) will introduce viable and hybrid platform that must be able to process the huge amount of data collected from multiple WBANs. This WBAN-cloud will enable users (including physicians and nurses) to globally access the processing and storage infrastructure at competitive costs. Because WBANs forward useful and life-critical information to the cloud – which may operate in distributed and hostile environments, novel security mechanisms are required to prevent malicious interactions to the storage infrastructure. Both the cloud providers and the users must take strong security measures to protect the storage infrastructure.

Cloud computing sobre a plataforma Windows Azure

A utilização massiva da internet e dos serviços que oferece por parte do utilizador final potencia a evolução dos mesmos, motivando as empresas a apostarem no desenvolvimento deste tipo de soluções. Requisitos como o poder de computação, flexibilidade e escalabilidade tornam-se cada vez mais indissociáveis do desenvolvimento aplicacional, o que leva ao surgimento de paradigmas como o de Cloud Computing. É neste âmbito que surge o presente trabalho. Com o objetivo de estudar o paradigma de Cloud Computing inicia-se um estudo sobre esta temática, onde é detalhado o seu conceito, a sua evolução histórica e comparados os diferentes tipos de implementações que suporta. O estudo detalha posteriormente a plataforma Azure, sendo analisada a sua topologia e arquitetura, detalhando-se os seus componentes e a forma como esta mitiga alguns dos problemas mencionados. Com o conhecimento teórico é desenvolvido um protótipo prático sobre esta plataforma, em que se exploram algumas das particularidades da topologia e se interage com as principais redes sociais. O estudo culmina com uma análise sobre os benefícios e desvantagens do Azure e através de um levantamento das necessidades da empresa, determinam-se as oportunidades que a utilização da plataforma poderá proporcionar.

Informal learning recognition through a cloud ecosystem

Learning and teaching processes, like all human activities, can be mediated through the use of tools. Information and communication technologies are now widespread within education. Their use in the daily life of teachers and learners affords engagement with educational activities at any place and time and not necessarily linked to an institution or a certificate. In the absence of formal certification, learning under these circumstances is known as informal learning. Despite the lack of certification, learning with technology in this way presents opportunities to gather information about and present new ways of exploiting an individual’s learning. Cloud technologies provide ways to achieve this through new architectures, methodologies, and workflows that facilitate semantic tagging, recognition, and acknowledgment of informal learning activities. The transparency and accessibility of cloud services mean that institutions and learners can exploit existing knowledge to their mutual benefit. The TRAILER project facilitates this aim by providing a technological framework using cloud services, a workflow, and a methodology. The services facilitate the exchange of information and knowledge associated with informal learning activities ranging from the use of social software through widgets, computer gaming, and remote laboratory experiments. Data from these activities are shared among institutions, learners, and workers. The project demonstrates the possibility of gathering information related to informal learning activities independently of the context or tools used to carry them out.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Remuneration and tariffs in the context of virtual power players

Power systems have been through deep changes in recent years, namely with the operation of competitive electricity markets in the scope and the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new player type which allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles, (V2G) and consumers), to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players` benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Energy and ancillary services joint market simulation

In order to develop a flexible simulator, a variety of models for Ancillary Services (AS) negotiation has been implemented in MASCEM – a multi-agent system competitive electricity markets simulator. In some of these models, the energy and the AS are addressed simultaneously while in other models they are addressed separately. This paper presents an energy and ancillary services joint market simulation. This paper proposes a deterministic approach for solving the energy and ancillary services joint market. A case study based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve, and Non-Spinning Reserve services is used to demonstrate that the use of the developed methodology is suitable for solving this kind of optimization problem. The presented case study is based on CAISO real AS market data considers fifteen bids.

Comparison between deterministic and meta-heuristic methods applied to ancillary services dispatch

This paper proposes two meta-heuristics (Genetic Algorithm and Evolutionary Particle Swarm Optimization) for solving a 15 bid-based case of Ancillary Services Dispatch in an Electricity Market. A Linear Programming approach is also included for comparison purposes. A test case based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is used to demonstrate that the use of meta-heuristics is suitable for solving this kind of optimization problem. Faster execution times and lower computational resources requirements are the most relevant advantages of the used meta-heuristics when compared with the Linear Programming approach.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Lipid content of frozen fish: comparison of different extraction methods and variability during freezing storage

In this work, a microwave-assisted extraction (MAE) methodology was compared with several conventional extraction methods (Soxhlet, Bligh & Dyer, modified Bligh & Dyer, Folch, modified Folch, Hara & Radin, Roese-Gottlieb) for quantification of total lipid content of three fish species: horse mackerel (Trachurus trachurus), chub mackerel (Scomber japonicus), and sardine (Sardina pilchardus). The influence of species, extraction method and frozen storage time (varying from fresh to 9 months of freezing) on total lipid content was analysed in detail. The efficiencies of methods MAE, Bligh & Dyer, Folch, modified Folch and Hara & Radin were the highest and although they were not statistically different, differences existed in terms of variability, with MAE showing the highest repeatability (CV = 0.034). Roese-Gottlieb, Soxhlet, and modified Bligh & Dyer methods were very poor in terms of efficiency as well as repeatability (CV between 0.13 and 0.18).

Estudo da implementação de um sistema de vigilância e alarme num recurso hídrico

Neste trabalho estudou-se a implementação de um sistema de vigilância e alerta da qualidade da água de um recurso hídrico, para um possível caso de poluição. Em 25 de Agosto de 2008 foram derramadas 4 toneladas de ácido clorídrico acidentalmente para as águas do rio Febros. Este rio situa-se no concelho de Vila Nova de Gaia e é um pequeno afluente do rio Douro, tendo cerca de 14 km de extensão e tem a particularidade de atravessar o Parque Biológico de Gaia. A falta de uma rápida intervenção e da existência de um plano de ação levou a que parte da fauna e flora fosse destruída. Por este motivo realizou-se este estudo que se baseou na criação de um sistema de vigilância e alerta a ser implementado neste rio. A informação da hidrogeometria do rio e da capacidade de transporte e dispersão de poluentes é indispensável para o bom funcionamento deste sistema. O coeficiente de dispersão longitudinal é um parâmetro muito importante no estudo da qualidade da água. Recorreu-se à utilização da Rodamina WT como marcador, determinando assim a evolução da sua concentração ao longo do tempo e espaço. No cálculo do coeficiente de dispersão foi utilizado o modelo Transient Storage, que demonstrou ser um bom modelo de ajuste aproximando-se dos valores medidos em campo. Para três estações diferentes com distâncias de 290, 390 e 1100 metros do ponto de injeção, obtiveram-se valores de coeficiente de dispersão de 0,18, 0,15 e 0,39 m2/s respetivamente. Os valores do ajuste expressos sob a forma de coeficiente de correlação foram 0,988, 0,998 e 0,986, para a mesma ordem de estações. A constante de rearejamento do rio foi também determinada recorrendo ao método dos marcadores inertes, utilizando o propano como marcador gasoso. A constante determinada próximo de Casal Drijo, entre 2 estações de amostragem a 140 e 290 m do local de injeção, foi de 13,4 dia-1. Com os resultados do coeficiente de dispersão e da constante de rearejamento para além da velocidade e caudal da corrente do rio conseguir-se-á construir o modelo de simulação e previsão de um possível poluente. O sistema de vigilância a implementar sugere-se assim que seja construído por duas partes, uma de análise de evolução da nuvem de poluição e plano de ação outra de monitorização contínua e emissão de alerta. Após uma análise do investimento à implementação deste sistema chegou-se à conclusão que o valor de investimento é de 15.182,00 €.

Transacção de componentes multimédia suportada por agentes

O objectivo do projecto descrito nesta dissertação é o desenvolvimento da interface entre as empresas e a plataforma Business-to-Business (B2B) de negociação automática de anúncios em construção. A plataforma, no seu todo, deve garantir que os intervalos da programação são preenchidos com um alinhamento de anúncios compatível com os interesses expressos e o perfil construído dos espectadores. A plataforma funciona como um mercado electrónico de negociação automática destinado a agências de publicidade (empresas produtoras) e empresas provedoras de conteúdos e serviços multimédia aos consumidores finais (empresas distribuidoras). As empresas, uma vez registadas na plataforma, passam a ser representadas por agentes que negoceiam automaticamente os itens submetidos com o comportamento especificado. Do ponto de vista da arquitectura, a plataforma consiste num sistema multiagente organizado em três camadas compostas por: (i) agentes de interface com as empresas; (ii) agentes de modelação das empresas; e (iii) agentes delegados, de duração efémera, exclusivamente criados para participar em negociações específicas de conteúdos multimédia. Cada empresa representada na plataforma possui, para além de um número indeterminado de delegados envolvidos em negociações específicas, dois agentes: (i) o agente de interface com a empresa, que expõe um conjunto de operações de interface ao exterior através de um serviço Web, localizado na primeira camada; e (ii) o agente que modela a empresa na plataforma, que expõe através de um serviço Web um conjunto de operações aos agentes das restantes camadas da plataforma, residente na camada intermédia. Este projecto focou-se no desenvolvimento da camada superior de interface da plataforma com as empresas e no enriquecimento da camada intermédia. A realização da camada superior incluiu a especificação da parte da ontologia da plataforma que dá suporte às operações de interface com o exterior, à sua exposição como serviços Web e à criação e controlo dos agentes de interface. Esta camada superior deve permitir às empresas carregar e descarregar toda informação relevante de e para a plataforma, através de uma interface gráfica ou de forma automática, e apresentar de forma gráfica e intuitiva os resultados alcançados, nomeadamente, através da apresentação da evolução das transacções. Em relação à camada intermédia, adicionou-se à ontologia da plataforma a representação do conhecimento de suporte às operações de interface com a camada superior, adoptaram-se taxonomias de classificação de espectadores, anúncios e programas, desenvolveu-se um algoritmo de emparelhamento entre os espectadores, programas e anúncios disponíveis e, por fim, procedeu-se ao armazenamento persistente dos resultados das negociações. Do ponto de vista da plataforma, testou-se o seu funcionamento numa única plataforma física e assegurou-se a segurança e privacidade da comunicação entre empresa e plataforma e entre agentes que representam uma mesma empresa.

Computação em nuvem: avaliação do retorno do investimento: o caso do Ensino Superior Português

Em Portugal, as instituições de ensino superior dispõem de plataformas de e-learning que reflectem uma mais-valia para o processo de ensino-aprendizagem. No entanto, estas plataformas caracterizam-se por serem de âmbito privado expondo, desta forma, a tímida abertura das instituições na partilha do seu conhecimento, como também dos seus recursos. O paradigma Cloud Computing surge como uma solução, por exemplo, para a criação de uma federação de nuvens capaz de contemplar soluções heterogéneas, garantindo a interoperabilidade entre as plataformas das várias instituições de ensino, e promovendo os objectivos propostos pelo Processo de Bolonha, nomeadamente no que se refere à partilha de informação, de plataformas e serviços e promoção de projectos comuns. Neste âmbito, é necessário desenvolver ferramentas que permitam aos decisores ponderar as mais-valias deste novo paradigma. Assim, é conveniente quantificar o retorno esperado para o investimento, em recursos humanos e tecnológicos, exigido pelo modelo Cloud Computing. Este trabalho contribui para o estudo da avaliação do retorno do investimento (ROI) em infra-estruturas e serviços TIC (Tecnologias de Informação e Comunicação), resultante da análise de diferentes cenários relativos à introdução do paradigma Cloud Computing. Para tal, foi proposta uma metodologia de análise baseada num questionário, distribuído por diversas instituições de ensino superior portuguesas, contendo um conjunto de questões que permitiram identificar indicadores, e respectivas métricas, a usar na elaboração de modelos de estimação do ROI.