Simulation relations, interface complexity, and resource optimality for real-time hierachical systems

Compositional schedulability analysis of hierarchical realtime systems is a well-studied problem. Various techniques have been developed to abstract resource requirements of components in such systems, and schedulability has been addressed using these abstract representations (also called component interfaces). These approaches for compositional analysis incur resource overheads when they abstract components into interfaces. In this talk, we define notions of resource schedulability and optimality for component interfaces, and compare various approaches.

Wind resource modelling in complex terrain using different mesoscale–microscale coupling techniques

Wind resource evaluation in two sites located in Portugal was performed using the mesoscale modelling system Weather Research and Forecasting (WRF) and the wind resource analysis tool commonly used within the wind power industry, the Wind Atlas Analysis and Application Program (WAsP) microscale model. Wind measurement campaigns were conducted in the selected sites, allowing for a comparison between in situ measurements and simulated wind, in terms of flow characteristics and energy yields estimates. Three different methodologies were tested, aiming to provide an overview of the benefits and limitations of these methodologies for wind resource estimation. In the first methodology the mesoscale model acts like “virtual” wind measuring stations, where wind data was computed by WRF for both sites and inserted directly as input in WAsP. In the second approach, the same procedure was followed but here the terrain influences induced by the mesoscale model low resolution terrain data were removed from the simulated wind data. In the third methodology, the simulated wind data is extracted at the top of the planetary boundary layer height for both sites, aiming to assess if the use of geostrophic winds (which, by definition, are not influenced by the local terrain) can bring any improvement in the models performance. The obtained results for the abovementioned methodologies were compared with those resulting from in situ measurements, in terms of mean wind speed, Weibull probability density function parameters and production estimates, considering the installation of one wind turbine in each site. Results showed that the second tested approach is the one that produces values closest to the measured ones, and fairly acceptable deviations were found using this coupling technique in terms of estimated annual production. However, mesoscale output should not be used directly in wind farm sitting projects, mainly due to the mesoscale model terrain data poor resolution. Instead, the use of mesoscale output in microscale models should be seen as a valid alternative to in situ data mainly for preliminary wind resource assessments, although the application of mesoscale and microscale coupling in areas with complex topography should be done with extreme caution.

Partial utility-driven scheduling for flexible SLA and pricing arbitration in clouds

Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads’ execution time is also improved, by incorporating an SLA-based redistribution of their VM’s computational power.

A genetic algorithm for the resource constrained multi-project scheduling problem

This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problem

This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

A two-level genetic algorithm for the multi-mode resource-constrained project scheduling problem

This paper presents a genetic algorithm for the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme by introducing an improvement procedure. It is evaluated the quality of the schedule and present detailed comparative computational results for the MRCPSP, which reveal that this approach is a competitive algorithm.

GIS from a cultural heritage perspective: when past and future collide

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

A resource for signs and Feynman diagrams of the standart model

When performing a full calculation within the standard model (SM) or its extensions, it is crucial that one utilizes a consistent set of signs for the gauge couplings and gauge fields. Unfortunately, the literature is plagued with differing signs and notations. We present all SM Feynman rules, including ghosts, in a convention-independent notation, and we table the conventions in close to 40 books and reviews.

Chaînes opératoires and resource-exploitation strategies in chimpanzee (Pan troglodytes) nut cracking

Journal of Human Evolution, V. 55, pp. 148-163

Uma metaheurística para a programação de projectos com multi-modos e recursos limitados

Este artigo apresenta uma nova abordagem (MM-GAV-FBI), aplicável ao problema da programação de projectos com restrições de recursos e vários modos de execução por actividade, problema conhecido na literatura anglo-saxónica por MRCPSP. Cada projecto tem um conjunto de actividades com precedências tecnológicas definidas e um conjunto de recursos limitados, sendo que cada actividade pode ter mais do que um modo de realização. A programação dos projectos é realizada com recurso a um esquema de geração de planos (do inglês Schedule Generation Scheme - SGS) integrado com uma metaheurística. A metaheurística é baseada no paradigma dos algoritmos genéticos. As prioridades das actividades são obtidas a partir de um algoritmo genético. A representação cromossómica utilizada baseia-se em chaves aleatórias. O SGS gera planos não-atrasados. Após a obtenção de uma solução é aplicada uma melhoria local. O objectivo da abordagem é encontrar o melhor plano (planning), ou seja, o plano que tenha a menor duração temporal possível, satisfazendo as precedências das actividades e as restrições de recursos. A abordagem proposta é testada num conjunto de problemas retirados da literatura da especialidade e os resultados computacionais são comparados com outras abordagens. Os resultados computacionais validam o bom desempenho da abordagem, não apenas em termos de qualidade da solução, mas também em termos de tempo útil.

A random key based genetic algorithm for the resource constrained project scheduling problem

This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Tecnologias multimédia no apoio ao ensino aprendizagem de suporte básico de vida

A sociedade moderna encontra-se numa evolução progressiva e vertiginosa nomeadamente no que respeita às novas tecnologias. Independentemente da área de conhecimento, é de senso comum que cada vez mais é necessária uma formação sólida, sendo fundamental a preparação e a consolidação das futuras gerações na utilização das novas tecnologias. As plataformas de e-learning são hoje em dia uma realidade mais que afirmada e com aplicação em todos os setores de atividade. Na área da saúde, e mais concretamente no que diz respeito ao tema de Suporte Básico de Vida (SBV), foi-nos possível verificar que a maioria das pessoas revela falta de conhecimentos sobre o tema e, não obstante existirem cursos sobre este tema, a disponibilidade para a sua frequência nem sempre é possível pela distância, falta de tempo e disponibilidade para a sua frequência, bem como pelos custos envolvidos. O presente estudo pretende contribuir para uma análise e investigação sobre o potencial de utilização das novas Tecnologias Multimédia, aplicando-as ao ensino concreto de primeiros socorros e especialmente de Suporte Básico de Vida, num recurso educativo digital com o formato de Objeto de Aprendizagem. Para o efeito, será construído um Objeto de Aprendizagem temático, focalizando o tema de SBV. O repositório MERLOT foi utilizado como meio de distribuição global, no sentido de aferir o potencial e facilidade de distribuição e catalogação com metadados. Foi ainda colocado on-line o “SBVOA” (Objeto de Aprendizagem desenvolvido no presente estudo), numa página criada apenas para o efeito. Esta dissertação apresenta o estudo desenvolvido para investigação do potencial de aprendizagem proporcionado pelo Objeto de Aprendizagem desenvolvido, validando se pode ser uma alternativa interativa de educação em SBV, contribuindo deste modo para a diminuição de eventuais perdas de vida.

Towards high-available and energy-efficient virtual computing environments in the cloud

Empowered by virtualisation technology, cloud infrastructures enable the construction of flexi- ble and elastic computing environments, providing an opportunity for energy and resource cost optimisation while enhancing system availability and achieving high performance. A crucial re- quirement for effective consolidation is the ability to efficiently utilise system resources for high- availability computing and energy-efficiency optimisation to reduce operational costs and carbon footprints in the environment. Additionally, failures in highly networked computing systems can negatively impact system performance substantially, prohibiting the system from achieving its initial objectives. In this paper, we propose algorithms to dynamically construct and readjust vir- tual clusters to enable the execution of users’ jobs. Allied with an energy optimising mechanism to detect and mitigate energy inefficiencies, our decision-making algorithms leverage virtuali- sation tools to provide proactive fault-tolerance and energy-efficiency to virtual clusters. We conducted simulations by injecting random synthetic jobs and jobs using the latest version of the Google cloud tracelogs. The results indicate that our strategy improves the work per Joule ratio by approximately 12.9% and the working efficiency by almost 15.9% compared with other state-of-the-art algorithms.

Conceção, seleção e implementação de um sistema de informação: ERP - enterprise resource planning

As organizações são entidades de natureza sistémica, composta, na sua maioria por várias pessoas que interagindo entre si, se propõem atingir objetivos comuns. Têm, frequentemente, de responder a alterações da envolvente externa através de processos de mudança organizacional, sendo fundamentalmente adaptativas, pois, para sobreviver, precisam de se reajustar continuamente às condições mutáveis do meio. O sucesso das organizações depende da sua capacidade de interação com o meio envolvente, ou seja, da sua capacidade de inovar e operar local ou globalmente, criando novas oportunidades de negócio que importa aproveitar. As tecnologias e os sistemas de informação e a forma como são utilizadas são fatores determinantes nesses processos de evolução e mudança. É necessário que a estratégia de TI esteja alinhada com os objetivos de negócio e que a sua utilização contribua para aumentos de produtividade e de eficiência no seu desempenho. Este trabalho descreve a análise, conceção, seleção e implementação de um Sistema de Informação na Portgás, S.A. baseado de um ERP - Enterprise Resource Planning, capaz de suportar a mudança organizacional e melhorar o desempenho global da organização. Promovendo numa primeira fase um crescimento exponencial do negócio e, de seguida, a adaptação da organização ao mercado concorrencial. O caso descreve o trabalho realizado pelo candidato e por equipas internas e externas, de levantamentos de requisitos gerais, técnicos e funcionais, desenvolvimento de um caderno de encargos, seleção, implementação e exploração de um ERP SAP. A apresentação e discussão do caso são enquadradas numa revisão de literatura sobre o papel das TI nos processos de mudança organizativa, alinhamento estratégico e vantagem competitiva das TI, contributo das TI para o aumento da produtividade, processos adoção e difusão das TI, fatores críticos de sucesso e BPM –Business Process Management

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.