Explorador integrado de serviços de armazenamento na cloud: cloud cockpit

Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Android as a cloud ticket validator

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Informática e de Computadores

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.

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

A checkpointing-enabled and resource-aware Java Virtual Machine for efficient and robust e-Science applications in grid environments

Object-oriented programming languages presently are the dominant paradigm of application development (e. g., Java,. NET). Lately, increasingly more Java applications have long (or very long) execution times and manipulate large amounts of data/information, gaining relevance in fields related with e-Science (with Grid and Cloud computing). Significant examples include Chemistry, Computational Biology and Bio-informatics, with many available Java-based APIs (e. g., Neobio). Often, when the execution of such an application is terminated abruptly because of a failure (regardless of the cause being a hardware of software fault, lack of available resources, etc.), all of its work already performed is simply lost, and when the application is later re-initiated, it has to restart all its work from scratch, wasting resources and time, while also being prone to another failure and may delay its completion with no deadline guarantees. Our proposed solution to address these issues is through incorporating mechanisms for checkpointing and migration in a JVM. These make applications more robust and flexible by being able to move to other nodes, without any intervention from the programmer. This article provides a solution to Java applications with long execution times, by extending a JVM (Jikes research virtual machine) with such mechanisms. Copyright (C) 2011 John Wiley & Sons, Ltd.

Broker colaborativo: gestão de recursos energéticos distribuídos

Neste trabalho é apresentado um Sistema de Informação (SI) cujo objetivo é contribuir para a colaboração entre VE possibilitando a sua entrada no mercado de energia elétrica, permiitindo deste modo que o proprietário do VE seja compensado. Esta compensação incidiria em medidas de minimização do investimento inicial na compra do VE e na criação de um modelo de armazenamento de energia mais sustentável. A este SI chamou-se de Broker Colaborativo ou simplesmente Broker e deverá permitir ao proprietário do VE criar um perfil com a sua informação pessoal, com informação do VE que possui e com informação relativa à colaboração que pretende efetuar, ou seja, locais e percentagem da bateria que pretende usar na colaboração. Para assegurar a entrada no mercado de energia torna-se necessário agrupar e filtrar um número significativo de VE, sendo essa responsabilidade atribuída ao Broker. Sendo a otimização do consumo de energia um fator importante neste trabalho, a implementação do Broker foi efetuada sobre o paradigma de Cloud Computing (será utilizada a designação abreviada de Cloud) onde os recursos energéticos são partilhados. A Clod possuiu uma grande capacidade de escalonamento onde se poderão criar os recursos à medida da necessidade. A utilização da Cloud permite que as especificações iniciais das máquinas virtuais, necessárias para alojar a base de dados ou os ficheiros do Broker, possam ser configuradas conforme o número de utilizadores do sistema. Assim, não se desperdiçam recursos que não seriam utilizados. Devido a estes aspetos dinâmicos, que estão intrínsecos ao fator humano, o Broker foi implementado utilizando um módulo de integração com a rede social Facebook esperando-se desta forma, que a colaboração entre diferentes VE seja difundida através dos amigos e conhecidos de cada utilizador da colaboração. Sendo assim, este trabalho pretende criar um sistema de informação onde os proprietários de VE possam juntar-se e criar uma colaboração possibilitando a sua entrada no mercado da energia elétrica. Essa colaboração será alargada recorrendo a uma rede social e compensada através de créditos. É abordado o tema das plataformas de Cloud como uma plataforma sustentável e vantajosa para o desenvolvimento de sistemas com grande potencial de crescimento.

Estudo e planeamento de uma infraestrutura computacional

As tecnologias de informação representam um pilar fundamental nas organizações como sustento do negócio através de infraestruturas dedicadas sendo que com o evoluir do crescimento no centro de dados surgem desafios relativamente a escalabilidade, tolerância à falha, desempenho, alocação de recursos, segurança nos acessos, reposição de grandes quantidades de informação e eficiência energética. Com a adoção de tecnologias baseadas em cloud computing aplica-se um modelo de recursos partilhados de modo a consolidar a infraestrutura e endereçar os desafios anteriormente descritos. As tecnologias de virtualização têm como objetivo reduzir a infraestrutura levantando novas considerações ao nível das redes locais e de dados, segurança, backup e reposição da informação devido á dinâmica de um ambiente virtualizado. Em centros de dados esta abordagem pode representar um nível de consolidação elevado, permitindo reduzir servidores físicos, portas de rede, cablagem, armazenamento, espaço, energia e custo, assegurando os níveis de desempenho. Este trabalho permite definir uma estratégia de consolidação do centro de dados em estudo que permita a tolerância a falhas, provisionamento de novos serviços com tempo reduzido, escalabilidade para mais serviços, segurança nas redes Delimitarized Zone (DMZ), e backup e reposição de dados com impacto reduzido nos recursos, permitindo altos débitos e rácios de consolidação do armazenamento. A arquitetura proposta visa implementar a estratégia com tecnologias otimizadas para o cloud computing. Foi realizado um estudo tendo como base a análise de um centro de dados através da aplicação VMWare Capacity Planner que permitiu a análise do ambiente por um período de 8 meses com registo de métricas de acessos, utilizadas para dimensionar a arquitetura proposta. Na implementação da abordagem em cloud valida-se a redução de 85% de infraestrutura de servidores, a latência de comunicação, taxas de transferência de dados, latências de serviços, impacto de protocolos na transferência de dados, overhead da virtualização, migração de serviços na infraestrutura física, tempos de backup e restauro de informação e a segurança na DMZ.

Benchmarking de uma aproximação de ticketing as a service (Taas)

Dissertação de natureza científica realizada para obtenção do grau de Mestre em Engenharia de Redes de Computadores e Multimédia

A bilhética dos transportes de passageiros na nuvem computacional

Relatório de Projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Trends Of CPU, GPU and FPGA for high-performance computing

Floating-point computing with more than one TFLOP of peak performance is already a reality in recent Field-Programmable Gate Arrays (FPGA). General-Purpose Graphics Processing Units (GPGPU) and recent many-core CPUs have also taken advantage of the recent technological innovations in integrated circuit (IC) design and had also dramatically improved their peak performances. In this paper, we compare the trends of these computing architectures for high-performance computing and survey these platforms in the execution of algorithms belonging to different scientific application domains. Trends in peak performance, power consumption and sustained performances, for particular applications, show that FPGAs are increasing the gap to GPUs and many-core CPUs moving them away from high-performance computing with intensive floating-point calculations. FPGAs become competitive for custom floating-point or fixed-point representations, for smaller input sizes of certain algorithms, for combinational logic problems and parallel map-reduce problems. © 2014 Technical University of Munich (TUM).

Simulation of a-Si PV system linked to the grid by DC boost and three-level inverter under cloud scope

This paper is about a PV system linked to the electric grid through power converters under cloud scope. The PV system is modeled by the five parameters equivalent circuit and a MPPT procedure is integrated into the modeling. The modeling for the converters models the association of a DC-DC boost with a three-level inverter. PI controllers are used with PWM by sliding mode control associated with space vector modulation controlling the booster and the inverter. A case study addresses a simulation to assess the performance of a PV system linked to the electric grid. Conclusions regarding the integration of the PV system into the electric grid are presented. © IFIP International Federation for Information Processing 2015.

Performance of coastal sea-defense infrastructure at El Jadida (Morocco) against tsunami threat: lessons learned from the Japanese 11 March 2011 tsunami

This paper seeks to investigate the effectiveness of sea-defense structures in preventing/reducing the tsunami overtopping as well as evaluating the resulting tsunami impact at El Jadida, Morocco. Different tsunami wave conditions are generated by considering various earthquake scenarios of magnitudes ranging from M-w = 8.0 to M-w = 8.6. These scenarios represent the main active earthquake faults in the SW Iberia margin and are consistent with two past events that generated tsunamis along the Atlantic coast of Morocco. The behavior of incident tsunami waves when interacting with coastal infrastructures is analyzed on the basis of numerical simulations of near-shore tsunami waves' propagation. Tsunami impact at the affected site is assessed through computing inundation and current velocity using a high-resolution digital terrain model that incorporates bathymetric, topographic and coastal structures data. Results, in terms of near-shore tsunami propagation snapshots, waves' interaction with coastal barriers, and spatial distributions of flow depths and speeds, are presented and discussed in light of what was observed during the 2011 Tohoku-oki tsunami. Predicted results show different levels of impact that different tsunami wave conditions could generate in the region. Existing coastal barriers around the El Jadida harbour succeeded in reflecting relatively small waves generated by some scenarios, but failed in preventing the overtopping caused by waves from others. Considering the scenario highly impacting the El Jadida coast, significant inundations are computed at the sandy beach and unprotected areas. The modeled dramatic tsunami impact in the region shows the need for additional tsunami standards not only for sea-defense structures but also for the coastal dwellings and houses to provide potential in-place evacuation.

Sensing Cloud Optimization to Solve ED of Units with Valve-Point Effects and Multi-fuels

In this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors "to fill" the search space and "guide" the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented.

A model for heterogeneous networks management and Performance evaluation

In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.

A biosignal embedded system for physiological computing

Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering