Campo do conhecimento: Enfoque na Modelagem Complexa ou Orientada a Objetos; Campo da comunicação humana:Diretrizes conceituais na modelagem complexa da comunicação humana , Canais Representacionais Mentais, Estilos de Aprender e Ensinar; Teste verificador dos canais representacionais; Teste verificador dos estilos pessoais; Exemplos práticos de utilização do conhecimento complexo na comunicação humana ; Trabalhando com a diversidade e suas potencialidades na comunicação interpessoal afetando positivamente o ambiente de trabalho; Conclusões e Orientações Práticas para o Desenvolvimento de Competências para o Profissional do século XXI.
http://ixa2.si.ehu.es/deep_learning_seminar/
Deep neural networks have boosted the convergence of multimedia data analytics in a unified framework shared by practitioners in natural language and vision. Image captioning, visual question answering or multimodal translation are some of the first applications of a new and exciting field that exploiting the generalization properties of deep neural representations. This talk will provide an overview of how vision and language problems are addressed with deep neural networks, and the exciting challenges being addressed nowadays by the research community.
https://telecombcn-dl.github.io/2019-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
https://mcv-m6-video.github.io/deepvideo-2019/
Overview of deep learning solutions for video processing. Part of a series of slides covering topics like action recognition, action detection, object tracking, object detection, scene segmentation, language and learning from videos.
Session 10 in module 3 from the Master in Computer Vision by UPC, UAB, UOC & UPF.
This lecture provides an overview of state of the art applications of convolutional neural networks to the problems in video processing: semantic recognition, optical flow estimation and object tracking.
https://mcv-m6-video.github.io/deepvideo-2019/
Overview of deep learning solutions for video processing. Part of a series of slides covering topics like action recognition, action detection, object tracking, object detection, scene segmentation, language and learning from videos.
Master in Computer Vision Barcelona, 2019
http://ixa2.si.ehu.es/deep_learning_seminar/
Deep neural networks have boosted the convergence of multimedia data analytics in a unified framework shared by practitioners in natural language and vision. Image captioning, visual question answering or multimodal translation are some of the first applications of a new and exciting field that exploiting the generalization properties of deep neural representations. This talk will provide an overview of how vision and language problems are addressed with deep neural networks, and the exciting challenges being addressed nowadays by the research community.
https://telecombcn-dl.github.io/2019-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
https://mcv-m6-video.github.io/deepvideo-2019/
Overview of deep learning solutions for video processing. Part of a series of slides covering topics like action recognition, action detection, object tracking, object detection, scene segmentation, language and learning from videos.
Session 10 in module 3 from the Master in Computer Vision by UPC, UAB, UOC & UPF.
This lecture provides an overview of state of the art applications of convolutional neural networks to the problems in video processing: semantic recognition, optical flow estimation and object tracking.
https://mcv-m6-video.github.io/deepvideo-2019/
Overview of deep learning solutions for video processing. Part of a series of slides covering topics like action recognition, action detection, object tracking, object detection, scene segmentation, language and learning from videos.
Master in Computer Vision Barcelona, 2019
https://imatge-upc.github.io/wav2pix/
Speech is a rich biometric signal that contains information about the identity, gender and emotional state of the speaker. In this work, we explore its potential to generate face images of a speaker by conditioning a Generative Adversarial Network (GAN) with raw speech input. We propose a deep neural network that is trained from scratch in an end-to-end fashion, generating a face directly from the raw speech waveform without any additional identity information (e.g reference image or one-hot encoding). Our model is trained in a self-supervised fashion by exploiting the audio and visual signals naturally aligned in videos. With the purpose of training from video data, we present a novel dataset collected for this work, with high-quality videos of ten youtubers with notable expressiveness in both the speech and visual signals.
These slides summarize the main trends in deep neural networks for video encoding. Including single frame models, spatiotemporal convolutionals, long term sequence modeling with RNNs and their combinaction with optical flow.
https://mcv-m6-video.github.io/deepvideo-2019/
These slides provides an overview of how deep neural networks can be used to solve an object tracking task
University Creates Flawless BYOD
Experience for Staff and Students. Cisco BYOD Smart Solution helps Brunel University provide network access
for 17,000 users across 70 buildings.
David Loureiro - Presentation at HP's HPC & OSL TESSysFera
David Loureiro, SysFera CEO, talks about "Managing large-scale, heterogeneous infrastructures: from DIET to SysFera-DS" at HP's High Performance Computing and Open Source & Linux Technical Excellence Symposium that took place on the 19-23 March, 2012, in Grenoble, France.
Social networks are a means to many ends, but using them correctly depends on many details of intended audiences and business goals. Cloud computing enables far more rapid adoption and business-focused deployment of secure, governable projects with compelling returns.
cloud computing - concepts and technologies and mechanisms of tackling problems in cloud
you plz ignore who created it , plz focus on problem oriented points
What the cloud has to do with a burning house?Nane Kratzke
Cloud native applications can create enormous business growth and value in a very short amount of time. Take Instagram as one example company. It took only two years to get a net asset value of 1 billion USD. However, cloud-native applications are often characterized by a highly implicit technological dependency on hosting cloud infrastructures. What happens if you are forced to leave your cloud service provider? What happens if your cloud is burning? The project Cloud TRANSIT investigates how to design cloud-native applications and services to reduce technological dependencies on underlying cloud infrastructures.
Adoption of Cloud Computing in Scientific ResearchYehia El-khatib
Some might say the scientific research community is somewhat behind the curve of adopting the cloud. In this talk, I present a few examples of adopting the cloud from the wider research community. I also highlight some of the aspects by which cloud computing could affect scientific research in the near future and the associated challenges.
Artificial intelligence in IoT-to-core network operations and managementADVA
Danish Rafique’s OFC 2019 presentation explores the AI application space and its architectural integration into today’s end-to-end network management stack.
https://imatge-upc.github.io/wav2pix/
Speech is a rich biometric signal that contains information about the identity, gender and emotional state of the speaker. In this work, we explore its potential to generate face images of a speaker by conditioning a Generative Adversarial Network (GAN) with raw speech input. We propose a deep neural network that is trained from scratch in an end-to-end fashion, generating a face directly from the raw speech waveform without any additional identity information (e.g reference image or one-hot encoding). Our model is trained in a self-supervised fashion by exploiting the audio and visual signals naturally aligned in videos. With the purpose of training from video data, we present a novel dataset collected for this work, with high-quality videos of ten youtubers with notable expressiveness in both the speech and visual signals.
These slides summarize the main trends in deep neural networks for video encoding. Including single frame models, spatiotemporal convolutionals, long term sequence modeling with RNNs and their combinaction with optical flow.
https://mcv-m6-video.github.io/deepvideo-2019/
These slides provides an overview of how deep neural networks can be used to solve an object tracking task
University Creates Flawless BYOD
Experience for Staff and Students. Cisco BYOD Smart Solution helps Brunel University provide network access
for 17,000 users across 70 buildings.
David Loureiro - Presentation at HP's HPC & OSL TESSysFera
David Loureiro, SysFera CEO, talks about "Managing large-scale, heterogeneous infrastructures: from DIET to SysFera-DS" at HP's High Performance Computing and Open Source & Linux Technical Excellence Symposium that took place on the 19-23 March, 2012, in Grenoble, France.
Social networks are a means to many ends, but using them correctly depends on many details of intended audiences and business goals. Cloud computing enables far more rapid adoption and business-focused deployment of secure, governable projects with compelling returns.
cloud computing - concepts and technologies and mechanisms of tackling problems in cloud
you plz ignore who created it , plz focus on problem oriented points
What the cloud has to do with a burning house?Nane Kratzke
Cloud native applications can create enormous business growth and value in a very short amount of time. Take Instagram as one example company. It took only two years to get a net asset value of 1 billion USD. However, cloud-native applications are often characterized by a highly implicit technological dependency on hosting cloud infrastructures. What happens if you are forced to leave your cloud service provider? What happens if your cloud is burning? The project Cloud TRANSIT investigates how to design cloud-native applications and services to reduce technological dependencies on underlying cloud infrastructures.
Adoption of Cloud Computing in Scientific ResearchYehia El-khatib
Some might say the scientific research community is somewhat behind the curve of adopting the cloud. In this talk, I present a few examples of adopting the cloud from the wider research community. I also highlight some of the aspects by which cloud computing could affect scientific research in the near future and the associated challenges.
Artificial intelligence in IoT-to-core network operations and managementADVA
Danish Rafique’s OFC 2019 presentation explores the AI application space and its architectural integration into today’s end-to-end network management stack.
Sabe aquele arquivo com 5000000 linhas e que você tem que acender umas velas pra abrir ele? Então, aqui te daremos as armas corretas para exterminá-lo e para NUNCA MAIS criar monstros como ele! A equipe Meritt irá mostrar como trazer para o cotidiano as práticas de clean code e o desafio de implementação em um projeto que já está no ar.
Atualmente, o Linux vem sendo utilizado como sistema operacional de tempo real, tanto
comercialmente quando academicamente. Esta apresentação introduz os conceitos básicos do Linux em tempo real, fazendo um paralelo com a teoria de sistemas de tempo real. Das implementações do kernel do Linux com características de tempo real, duas são apresentadas: o PREEMPT_RT, a alternativa comercial, e o LitmusRT, a alternativa acadêmica. Para cada implementação, são apresentados detalhes de sua implementação e exemplos de pesquisas que estão sendo desenvolvidas atualmente nestes sistemas.
Cooperação e Codificação de Rede Aplicadas as RSSF IndustriaisPET Computação
As Redes de Sensores sem Fio (RSSF) vem apresentando uma penetração cada vez maior nas mais distintas áreas, dada a sua versatilidade e baixo custo. Mais recentemente foi proposto seu emprego no chão de fábrica, com o surgimento de diversos padrões específicos, com especial destaque ao padrão IEEE 802.15.4. O ambiente industrial possui características específicas que requerem cuidado na aplicação das RSSF: requisitos de tempo real e alto índice de ruído eletromagnético. Sendo assim, é determinante para RSSF industriaias que se maximize a confiabilidade na troca de mensagens. Uma das propostas neste sentido é o emprego de técnicas de cooperação e codificação de rede.
Redes de Sensores e Robôs: Um novo paradigma de Monitoramento e AtuaçãoPET Computação
O advento da computação embarcada permitiu o surgimento de tecnologias inovadoras tais como as redes de sensores sem fio (rssf). Uma RSSF é composta por nodos de tamanho reduzido com capacidade de sensoriamento e comunicação sem fio. Uma segunda evolução desta tecnologia é a integração de RSSF com robôs móveis – as redes de sensores e robôs. Estes robôs (aéreos, terrestres ou aquáticos) são capazes de coletar dados de nodos sensores estacionários ou de interagirem com outros robôs móveis formando esquadrôes ou times de nodos sensores móveis. Nesta palestra serão apresentadas as tendências deste novo paradigma de computação móvel.
Hoje em dia é fácil juntar quantidades absurdamente grandes de dados. Mas, uma vez de posse deles, como fazer para extrair informações dessas montanhas amorfas de dados? Nesse minicurso vamos apresentar o modelo de programação MapReduce: entender como ele funciona, para que serve e como construir aplicações usando-o. Vamos ver também como usar o Elastic MapReduce, o serviço da Amazon que cria clusters MapReduce sob-demanda, para que você não se preocupe em administrar e conseguir acesso a um cluster de máquinas, mas em como fazer seu código digerir de forma distribuída os dados que você possui. Veremos exemplos práticos em ação e codificaremos juntos alguns desafios.
Processamento e visualização tridimensional de imagens de Satelite e RadarPET Computação
Com o avanço das tecnologias de imageamento para a área de previsão meteorológica, o processamento de imagens e computação gráfica tem permitido melhorar a qualidade dos resultados no que tange aspectos de interpretação e visualização. O INCoD tem trabalhado com pesquisas e desenvolvimento inovadoras nesta área. Estas soluções são executadas em parceria com o INPE, CEMADEN e EPAGRI gerando ferramentas que auxiliam os meteorologistas e climatologistas a melhorar as previsões.
Software Evolution: From Legacy Systems, Service Oriented Architecture to Clo...PET Computação
There is more to software life cycle than just software development. Software development happens once, then evolution takes up the bulk of the software life cycle. In this presentation, I will talk about some approaches needed to deal with legacy systems. This is to aid their update to new business and maintenance requirements in addition to their upgrade to continuous new technologies. Service oriented architecture will be presented to support software evolution in this fast, ever changing environment. Moreover, cloud computing that enables ubiquitous and on demand access to computing resources will be examined. Applied research, such as in health care and M2M domains, involving these innovative technologies will be presented to illustrate their benefits to the advancement of software engineering.
O desenvolvimento de soluções para problemas não-triviais exige, primeiramente, o estudo minucioso das características intrínsecas destes problemas e determinar o conjunto de ações que quando executadas em uma sequência lógica alcançam tais soluções.Planejamento Automático é uma área da Inteligência Artificial que estuda as formas adequadas de representação do conhecimento e mecanismos eficientes que permitem a agentes inteligentes raciocinar automaticamente as soluções de problemas complexos.Técnicas de Planejamento Automático são utilizadas em diversas áreas principalmente as ligadas às Engenharias, tratando problemas que envolvem alto custo, alto risco e sujeitos a restrições.Especificamente em robótica, o Planejamento Automático é aplicado tanto na construção de planos que regem a movimentação do robô quanto em nível cognitivo, onde constitui-se no processo de raciocínio deliberativo, que promove autonomia ao agente robótico. Esta palestra tem por objetivo apresentar uma visão geral da área de Planejamento Automático, abordando as suas principais técnicas, em especial a técnica que trata problemas de planejamento como um problema de satisfazibilidade em uma fórmula em lógica proposicional.
Como utilizamos um serviço de cloud para validar nossas estimativas de escalabilidade. Rodando o sistema inteiro, mais clientes de teste, num cloud a baixíssimo custo.
Bancos de dados nas nuvens: uma visão geralPET Computação
O paradigma de computação nas nuvens vem ganhando popularidade uma vez que permite a aplicações utilizar recursos computacionais remotos a custo baixo e, com isso, minimizar esforços com desenvolvimento e manutenção destes recursos no seu ambiente local. Este paradigma também está se tornando presente na área de Banco de Dados, motivado pela necessidade de gerência de um grande volume de dados pelas organizações a baixo custo. Os tradicionais bancos de dados relacionais deixam a desejar neste quesito. Esta palestra apresenta uma visão geral de bancos de dados na nuvem, enfatizando suas principais características, categorias (incluindo os bancos de dados NoSQL) e tendências de pesquisa.
Uma reflexão sobre os 28 anos de pesquisa no laboratório de integração de sof...PET Computação
O Laboratório de Integração de Software e Harwdware da UFSC foi fundado em março de 1984 com a missão de desenvolver pesquisas na fronteira entre hardware e software. Desde então, vem desenvolvendo soluções inovadoras para o desenvolvimento de sistemas computacionais dedicados através da agregação de componentes de hardware e de software previamente validados. Esta caminhada conduziu o grupo por importantes áreas de aplicação, incluindo redes de computadores, telemedicina, televisão digital, telecomunicações e, mais recentemente, cidades inteligentes, smart grid e a Internet das coisas. Prestes a completarem 30 anos, tem nesta apresentação uma reflexão sobre a caminhada até o presente com o objetivo de traçar diretrizes para o futuro próximo.
Rastreamento de objetos utilizando ar dronePET Computação
Este projeto visa utilizar-se de tecnologias de processamento de imagens e reconhecimento de padrões para encontrar e rastrear um determinado objeto. Utiliza-se técnicas avançadas de classificação de padrões de cores, tais como o Polynomial Mahalanobis para identificar o alvo e rastreá-lo. O rastreamento é feito por um equipamento de vôo quadrirotor AR.Drone Parriot.
Processamento e visualização tridimensional de imagens de satelite e radarPET Computação
Com o avanço das tecnologias de imageamento para a área de previsão meteorológica, o processamento de imagens e computação gráfica tem permitido melhorar a qualidade dos resultados no que tange aspectos de interpretação e visualização. O INCoD tem trabalhado com pesquisas e desenvolvimento inovadoras nesta área. Estas soluções são executadas em parceria com o INPE, CEMADEN e EPAGRI gerando ferramentas que auxiliam os meteorologistas e climatologistas a melhorar as previsões.
Evoluindo dot project em alinhamento ao pmbokPET Computação
Projetos de software frequentemente falham, pois não são gerenciados de maneira adequada. Buscando reduzir este problema, modelos de boas práticas, como o CMMI - Capability Maturity Model Integration e o PMBOK - Project Management Body of Knowledge são desenvolvidos para auxiliar as organizações a melhorarem seu processo de gerenciamento de projetos. Entretanto, ainda não existe nenhuma ferramenta de suporte de software livre para suportar completamente um processo de gerência de projeto em conformidade com esses modelos. Dentro desse o contexto, a palestra apresentará a evolução da ferramenta dotProject relacionados a diversas áreas (iniciação, planejamento de tempo, RH e riscos, monitoramento & controle e encerramento) alinhado ao CMMI e PMBOK.
O uso de jogos para o ensino tem se tornado cada vez mais popular - inclusive no ensino da Computação. Sua utilização permite obter consideráveis melhorias nos resultados da aprendizagem como: aumento no aprendizado efetivo, melhoras no interesse e motivação, redução do tempo de formação e redução da necessidade de instrutores. No entanto, para efetivamente adotar jogos educacionais na prática, instrutores atualmente enfrentam diversas dificuldades, como a carência destes conteúdos na literatura e a carência de processos para o desenvolvimento de jogos educacionais. Neste contexto, a palestra apresenta os resultados das pesquisas com jogos aplicados ao ensino em computação.
Apresentação geral do gqs - Usabilidade na convergência digital - Customizaç...PET Computação
O GQS - Grupo de Qualidade de Software concentra-se na pesquisa científica, desenvolvimento e transferência de modelos, métodos e ferramentas de engenharia de software para apoiar a melhoria da qualidade de processos e produtos de software principalmente voltados ao contexto de micro e pequenas empresas. As áreas de pesquisa incluem melhoria e avaliação de processo de software (CMMI - ISO / IEC 15504/12207 - MPS.BR), gerenciamento de projetos de software, educação de engenharia de software e engenharia de usabilidade.
LaTeX é um sistema para preparação de textos que, ao contrário dos softwares mais comuns de edição de textos como LibreOffice Writer e MS Office Word, permite que o escritor mantenha o foco no conteúdo e na semântica do que se escreve e não no formato e na aparência ao mesmo tempo em que garante um resultado final de alta qualidade tipográfica. Este minicurso terá foco na preparação de textos (artigos, relatórios) e nas ferramentas que possam ser necessárias, e.g. inclusão de imagens, formatação de referências, fórmulas matemáticas.
Git é uma ferramenta de controle de versão distribuída que é muito usada em projetos open source e que propõe ser eficiente e simples. O minicurso terá um caráter prático, abordando as principais ações, problemas encontrados (conflitos) e uso de servidores remotos (github).
Com a cabeça nas nuvens: montando ambientes para aplicações elásticasPET Computação
Muito se fala sobre o desenvolvimento de aplicações escaláveis e elásticas que possam se adaptar à grande flutuação do volume de acesso no decorrer do dia. A infraestrutura para que esse ambiente possa funcionar, entretanto, é de igual importância. Nesse minicurso vamos lançar dezenas de servidores na cloud da Amazon para que uma aplicação possa escalar facilmente sem nenhuma preocupação.
Redes de sensores sem fio autonômicas: abordagens, aplicações e desafiosPET Computação
Este curso tem como principal objetivo apresentar aos ouvintes conceitos sobre redes de sensores sem fio (RSSF), protocolos de comunicação para RSSF e conceitos de computação autonômica. Além disso, aplicações focadas nas áreas de monitoramento ambiental, agricultura de precisão, segurança e defesa também serão apresentados.
Redes de sensores sem fio autonômicas: abordagens, aplicações e desafios
Cloud computing: evolution or redefinition
1. 11/10/2012
This talk addresses fundamental concepts of cloud computing
which are related to parallel and distributed environments.
Cloud Computing: This is followed by a discussion of challenges faced by this
computational paradigm in order to meet the requirements of
Evolution or Redefinition applications from different domains.
Additionally, limitations of the cloud computing paradigm
will be highlightedand finally commercial and
academic study cases will be presented.
Prof. Mario Dantas
Federal University of Santa Catarina (UFSC)
Informatics and Statistics Department (INE)
Florianópolis - Brazil
E-mail: mario.dantas@ufsc.br
Motivation for this talk Motivation for this talk
a) Internet x Web b) Downsizing x Rightsizing (90's)
Number of computers connected to the internet
From centralised environments to distributed computing
Date Computers Web Server
1979, Dec 188 0
1989,July 130,000 0
1999, July 56,218,000 5,560,866
Motivation for this talk Motivation for this talk
c) Unix x Linux d) wired x wireless networks (90's and early 00's)
Standards (BSD and AT&T) against standard Reliable, high speed links against unsecure and slow
networks
1
2. 11/10/2012
Motivation for this talk Motivation for this talk
e) HPC x Cloud Environments f) Academic x Commercial Approach
Are these environments excludents Several challenges in the computer industry
or complementaries paradigms? were studied in the past with an initial collaboration
from the academic community.
BUT, without this approach we can have figures like these:
Motivation for this talk Agenda
> Concepts
g) A special user view > Challenges
“I’ve never seen something more powerful than this computation combined with > Requirements
this network that we now have...
In the last seven years, do you know how many times
I’ve lost any personal data? Zero. Do you know how many times I’ve backed up > Limitations
my computer? Zero.” – Steve Jobs, 1997.
> Study Cases
> Conclusions and Recommendations
Concepts
Agenda
l Architecture evolution
> Concepts
Von Neumann Architecture
> Challenges
l
> Requirements
> Limitations • CPU • Memory l Main bus
> Study Cases
> Conclusions and Recommendations
l I/O bus
• Output • Input
• Device • Device
2
3. 11/10/2012
Concepts Concepts
l Architecture evolution l Architecture evolution
l Fermi Architecture
l Old fashion clusters
l Source: [www.nvidia.com]
Concepts Concepts
l Architecture evolution
l Cloud computing buzzwords
l PaaS l PaaS l SaaS
• Remote Viz.
• Groupware
• Virtualization
• • Web Portal
• Collaboration l EC2 l Google
l APPs
l Private
l Public
l Cloud
l Cloud
• [Dominic Lam, IBM]
Concepts Concepts
Cloud computing is a model
But, how can we understand these > for enabling ubiquitous, convenient, on-demand network
cloud buzzwords? access to a shared pool of configurable computing resources
(e.g., networks, servers, storage, applications, and services)
> that can be rapidly provisioned and released with minimal
management effort or service provider interaction.
3
4. 11/10/2012
Concepts Concepts
Essential Characteristics:
This cloud model is composed of:
1) On-demand self-service;
> five essential characteristics;
> three service models; and 2) Broad network access;
> four deployment models.
3) Resource pooling;
4) Rapid elasticity;
5) Measured service.
Concepts Concepts
Service Model:
1) SaaS (Software as a Service);
2) PaaS (Plataform as a Service);
3) IaaS (Infrastructure as a Service).
l [Zhang, Cheng, Boutaba, 2010]
Concepts Concepts
Service Model
4
5. 11/10/2012
Concepts Concepts
Deployment Models:
1) Private cloud. The cloud infrastructure is provisioned for But, is this idea of cloud effort new?
exclusive use by a single organization
2) Community cloud. The cloud infrastructure is provisioned “We will probably see the spread of ‘computer utilities’, w
for exclusive use by a specific community of consumers like present electric and telephone utilities, will service
Individual homes and offices across the country.”
3) Public cloud. The cloud infrastructure is provisioned for [1969, Len Kleinrock]
open use by the general public
4) Hybrid cloud. The cloud infrastructure is a composition
of two or more distinct cloud infrastructures
Concepts
Agenda
> Concepts
“A computational grid is a hardware and software > Challenges
infrastructure that provides dependable, consistent,
pervasive, and inexpensive access to high-end computational > Requirements
capabilities.”
> Limitations
> Study Cases
[1998, Ian Foster and Carl Kesselman]
> Conclusions and Recommendations
Challenges Challenges
But, does the cloud approach have any challenge?
Essential characteristics Examples to remember
But, does the cloud approach have any challenge?
1) On-demand self-service; Self-service restaurant queues;
2) Broad network access; Different roads from different
states/provinces/countries;
3) Resource pooling; Shared or distributed memory;
4) Rapid elasticity; EURO monetary elasticity;
5) Measured service. bills never delay.
5
6. 11/10/2012
Challenges
Agenda
> Interoperability: Lack of (or to many) standards; > Concepts
> Challenges
> Human Resources: Small number of people with real
good knowledge of distributed systems; > Requirements
> Limitations
> Security : . Byzantines attacks; > Study Cases
. not yet known......
(e.g. Cyber attacks such as Stuxnet and flame) > Conclusions and Recommendations
Requirements Requirements
Deployment Models:
But, which are the requirements 1) Private cloud. It may be owned, managed,
to have a cloud environment? and operated by the organization, a third party, or some
combination of them, and it may exist on or off premises.
2) Community cloud. It may be owned, managed, and
operated by one or more of the organizations in the
community, a third party, or some combination of them,
and it may exist on or off premises.
Requirements
Agenda
> Concepts
Deployment Models:
> Challenges
> Requirements
3) Public cloud. It may be owned, managed, and
operated by a business, academic, or government > Limitations
organization, or some combination of them. It
exists on the premises of the cloud provider. > Study Cases
4) Hybrid cloud. cloud infrastructures (private, > Conclusions and Recommendations
community, or public) that remain unique entities,
but are bound together by standardized or proprietary
technology that enables data and application portability
(e.g., cloud bursting for load balancing between clouds).
6
7. 11/10/2012
Limitations Limitations
> Heterogeneity: cloud providers facilities;
But, does the cloud computing approach
> Elasticity: this number is not known yet;
have any limitation?
> (full) Interoperability: between low level
applications (e.g. virtual machine tools);
> Human resources: developers for this
Hybrid environment (shared, distributed
memory and GPU environments)
Agenda
> Concepts Study Cases
> Challenges
Public Clouds
> Requirements
> Limitations
> Study Cases
> Conclusions and Recommendations
Study Cases
l Public Clouds
l [Zhang, Cheng, Boutaba, 2010]
7
8. 11/10/2012
Study Cases
l AZURE (PaaS)
Study Cases Study Cases
l S3 (PaaS)
l S3 (PaaS)
l Source: [www.amazon.com] l Source: [www.amazon.com]
Study Cases
l [Zhang, Cheng, Boutaba, 2010]
Study Cases
Private Clouds
(UFSC/CTC/INE/LaPeSD)
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Study Cases Study Cases
Private Clouds
(UFSC/CTC/INE/LaPeSD) l System
l Interface l Management
l Provisioning
l Tools
l Monitoring
l Services l Private Cloud
l Catalog
l [Dantas et al., 2009]
Study Cases Study Cases
l A) Context oriented approach Resource Reservation
Study Cases Study Cases
User Centric Authentication
Spatio-Temporal Model
l
l
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Study Cases Study Cases
l Experimental Results l Experimental Results
l Experimento 1 – Comparação das abordagens de l Experimento 2 – Comparação da eficiência das
autenticação adotando o consumo energético como abordagens de autenticação em termos percentuais
métrica
Study Cases Study Cases
l B) Ontology Approach l Ontology Approach
l Reference Brazil Canada
l VO-C l # processors l VO-B l # processors
l Cluster_01 l 7 l Cluster_1 l 4
l Cluster_02 l 5 l Cluster_2 l 4
l Cluster_03 l 3 l - l -
l Multi-cluster (cloud) configuration
l [Dantas et al., 2009] l [Dantas et al., 2009]
Study Cases Study Cases
Experimental Results Experimental Results
• Interactive Interface • Interactive Interface
• Test without dynamic information
• Test with dynamic information
l [Dantas et al., 2009] l [Dantas et al., 2009]
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Study Cases Study Cases
Experimental Results Experimental Results
• Interactive Interface • Interactive Interface
• No dynamic information considered
• Dynamic Information
l [Dantas et al., 2009]
l [Dantas et al., 2009]
Study Cases
Agenda
C) Advance reservation of resources through augmented reality > Concepts
> Challenges
> Requirements
> Limitations
> Study Cases
> Conclusions and Recommendations
a.b. This centralized environment adopts
several approaches from:
a. > computer architecture;
a. The cloud approach can be considered now as
redefinition on how to use several existing a. > computer networks:
paradigms, such as:
a.> distributed and parallel computing
Grid computing; b. paradigms;
l Utility computing;
l Virtualization;
l Autonomic computing.
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a.c. The cloud approach has some news d. The cloud approach in the future could be
challenges to be considered in large scale: a. considered as an Evolution. if the used
paradigms form a new approach
a.> heterogemeity (hw & sw);
a.> security; and
a.> mobile computing interaction.
• Recomendations • Recomendations
• Consider multi- disciplinary subjects, such as: • When developing to cloud environments, do'nt forget:
DB; > The context aware, ontology and fault tolerance approaches;
> How a better computing performance can help
Distributed systems (e.g. Mosix, Condor);
(e.g. speed up web paradigm);
Mobile computing (e.g. sensors); > Mobility facilities;
Programming languages (e.g. CUDA, PGAS); > Security issues.
●Computer newtorks (e.g. Infiniband, Quadrics);
● Computer architectures (e.g.multi-computers, multi-procesores);
Cloud Computing:
Evolution or Redefinition
QUESTIONS?
Prof. Mario Dantas
Federal University of Santa Catarina (UFSC)
Informatics and Statistics Department (INE)
Florianópolis - Brazil
E-mail: mario.dantas@ufsc.br
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