704 resultados para cloud computing, hypervisor, virtualizzazione, live migration, infrastructure as a service


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Nella fisica delle particelle, onde poter effettuare analisi dati, è necessario disporre di una grande capacità di calcolo e di storage. LHC Computing Grid è una infrastruttura di calcolo su scala globale e al tempo stesso un insieme di servizi, sviluppati da una grande comunità di fisici e informatici, distribuita in centri di calcolo sparsi in tutto il mondo. Questa infrastruttura ha dimostrato il suo valore per quanto riguarda l'analisi dei dati raccolti durante il Run-1 di LHC, svolgendo un ruolo fondamentale nella scoperta del bosone di Higgs. Oggi il Cloud computing sta emergendo come un nuovo paradigma di calcolo per accedere a grandi quantità di risorse condivise da numerose comunità scientifiche. Date le specifiche tecniche necessarie per il Run-2 (e successivi) di LHC, la comunità scientifica è interessata a contribuire allo sviluppo di tecnologie Cloud e verificare se queste possano fornire un approccio complementare, oppure anche costituire una valida alternativa, alle soluzioni tecnologiche esistenti. Lo scopo di questa tesi è di testare un'infrastruttura Cloud e confrontare le sue prestazioni alla LHC Computing Grid. Il Capitolo 1 contiene un resoconto generale del Modello Standard. Nel Capitolo 2 si descrive l'acceleratore LHC e gli esperimenti che operano a tale acceleratore, con particolare attenzione all’esperimento CMS. Nel Capitolo 3 viene trattato il Computing nella fisica delle alte energie e vengono esaminati i paradigmi Grid e Cloud. Il Capitolo 4, ultimo del presente elaborato, riporta i risultati del mio lavoro inerente l'analisi comparata delle prestazioni di Grid e Cloud.

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Nowadays, data handling and data analysis in High Energy Physics requires a vast amount of computational power and storage. In particular, the world-wide LHC Com- puting Grid (LCG), an infrastructure and pool of services developed and deployed by a ample community of physicists and computer scientists, has demonstrated to be a game changer in the efficiency of data analyses during Run-I at the LHC, playing a crucial role in the Higgs boson discovery. Recently, the Cloud computing paradigm is emerging and reaching a considerable adoption level by many different scientific organizations and not only. Cloud allows to access and utilize not-owned large computing resources shared among many scientific communities. Considering the challenging requirements of LHC physics in Run-II and beyond, the LHC computing community is interested in exploring Clouds and see whether they can provide a complementary approach - or even a valid alternative - to the existing technological solutions based on Grid. In the LHC community, several experiments have been adopting Cloud approaches, and in particular the experience of the CMS experiment is of relevance to this thesis. The LHC Run-II has just started, and Cloud-based solutions are already in production for CMS. However, other approaches of Cloud usage are being thought of and are at the prototype level, as the work done in this thesis. This effort is of paramount importance to be able to equip CMS with the capability to elastically and flexibly access and utilize the computing resources needed to face the challenges of Run-III and Run-IV. The main purpose of this thesis is to present forefront Cloud approaches that allow the CMS experiment to extend to on-demand resources dynamically allocated as needed. Moreover, a direct access to Cloud resources is presented as suitable use case to face up with the CMS experiment needs. Chapter 1 presents an overview of High Energy Physics at the LHC and of the CMS experience in Run-I, as well as preparation for Run-II. Chapter 2 describes the current CMS Computing Model, and Chapter 3 provides Cloud approaches pursued and used within the CMS Collaboration. Chapter 4 and Chapter 5 discuss the original and forefront work done in this thesis to develop and test working prototypes of elastic extensions of CMS computing resources on Clouds, and HEP Computing “as a Service”. The impact of such work on a benchmark CMS physics use-cases is also demonstrated.

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Um das principais características da tecnologia de virtualização é a Live Migration, que permite que máquinas virtuais sejam movimentadas entre máquinas físicas sem a interrupção da execução. Esta característica habilita a implementação de políticas mais sofisticadas dentro de um ambiente de computação na nuvem, como a otimização de uso de energia elétrica e recursos computacionais. Entretanto, a Live Migration pode impor severa degradação de desempenho nas aplicações das máquinas virtuais e causar diversos impactos na infraestrutura dos provedores de serviço, como congestionamento de rede e máquinas virtuais co-existentes nas máquinas físicas. Diferente de diversos estudos, este estudo considera a carga de trabalho da máquina virtual um importante fator e argumenta que escolhendo o momento adequado para a migração da máquina virtual pode-se reduzir as penalidades impostas pela Live Migration. Este trabalho introduz a Application-aware Live Migration (ALMA), que intercepta as submissões de Live Migration e, baseado na carga de trabalho da aplicação, adia a migração para um momento mais favorável. Os experimentos conduzidos neste trabalho mostraram que a arquitetura reduziu em até 74% o tempo das migrações para os experimentos com benchmarks e em até 67% os experimentos com carga de trabalho real. A transferência de dados causada pela Live Migration foi reduzida em até 62%. Além disso, o presente introduz um modelo que faz a predição do custo da Live Migration para a carga de trabalho e também um algoritmo de migração que não é sensível à utilização de memória da máquina virtual.

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To benefit from the advantages that Cloud Computing brings to the IT industry, management policies must be implemented as a part of the operation of the Cloud. Among others, for example, the specification of policies can be used for the management of energy to reduce the cost of running the IT system or also for security policies while handling privacy issues of users. As cloud platforms are large, manual enforcement of policies is not scalable. Hence, autonomic approaches for management policies have recently received a considerable attention. These approaches allow specification of rules that are executed via rule-engines. The process of rules creation starts by the interpretation of the policies drafted by high-rank managers. Then, technical IT staff translate such policies to operational activities to implement them. Such process can start from a textual declarative description and after numerous steps terminates in a set of rules to be executed on a rule engine. To simplify the steps and to bridge the considerable gap between the declarative policies and executable rules, we propose a domain-specific language called CloudMPL. We also design a method of automated transformation of the rules captured in CloudMPL to the popular rule-engine Drools. As the policies are changed over time, code generation will reduce the time required for the implementation of the policies. In addition, using a declarative language for writing the specifications is expected to make the authoring of rules easier. We demonstrate the use of the CloudMPL language into a running example extracted from a management energy consumption case study.

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Cloud computing enables independent end users and applications to share data and pooled resources, possibly located in geographically distributed Data Centers, in a fully transparent way. This need is particularly felt by scientific applications to exploit distributed resources in efficient and scalable way for the processing of big amount of data. This paper proposes an open so- lution to deploy a Platform as a service (PaaS) over a set of multi- site data centers by applying open source virtualization tools to facilitate operation among virtual machines while optimizing the usage of distributed resources. An experimental testbed is set up in Openstack environment to obtain evaluations with different types of TCP sample connections to demonstrate the functionality of the proposed solution and to obtain throughput measurements in relation to relevant design parameters.

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Despite the compelling case for moving towards cloud computing, the upstream oil & gas industry faces several technical challenges—most notably, a pronounced emphasis on data security, a reliance on extremely large data sets, and significant legacy investments in information technology (IT) infrastructure—that make a full migration to the public cloud difficult at present. Private and hybrid cloud solutions have consequently emerged within the industry to yield as much benefit from cloud-based technologies as possible while working within these constraints. This paper argues, however, that the move to private and hybrid clouds will very likely prove only to be a temporary stepping stone in the industry’s technological evolution. By presenting evidence from other market sectors that have faced similar challenges in their journey to the cloud, we propose that enabling technologies and conditions will probably fall into place in a way that makes the public cloud a far more attractive option for the upstream oil & gas industry in the years ahead. The paper concludes with a discussion about the implications of this projected shift towards the public cloud, and calls for more of the industry’s services to be offered through cloud-based “apps.”

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Cloud Computing, based on early virtual computer concepts and technologies, is now itself a maturing technology in the marketplace and it has revolutionized the IT industry, being the powerful platform that many businesses are choosing to migrate their in-premises IT services onto. Cloud solution has the potential to reduce the capital and operational expenses associated with deploying IT services on their own. In this study, we have implemented our own private cloud solution, infrastructure as a service (IaaS), using the OpenStack platform with high availability and a dynamic resource allocation mechanism. Besides, we have hosted unified communication as a service (UCaaS) in the underlying IaaS and successfully tested voice over IP (VoIP), video conferencing, voice mail and instant messaging (IM) with clients located at the remote site. The proposed solution has been developed in order to give advice to bussinesses that want to build their own cloud environment, IaaS and host cloud services and applicatons in the cloud. This paper also aims at providing an alternate option for proprietary cloud solutions for service providers to consider.

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The future of civic engagement is characterised by both technological innovation as well as new technological user practices that are fuelled by trends towards mobile, personal devices; broadband connectivity; open data; urban interfaces; and, cloud computing. These technology trends are progressing at a rapid pace, and have led global technology vendors to package and sell the ‘Smart City’ as a centralized service delivery platform predicted to optimize and enhance cities’ key performance indicators – and generate a profitable market. The top-down deployment of these large and proprietary technology platforms have helped sectors such as energy, transport, and healthcare to increase efficiencies. However, an increasing number of scholars and commentators warn of another ‘IT bubble’ emerging. Along with some city leaders, they argue that the top-down approach does not fit the governance dynamics and values of a liberal democracy when applied across sectors. A thorough understanding is required, of the socio-cultural nuances of how people work, live, play across different environments, and how they employ social media and mobile devices to interact with, engage in, and constitute public realms. Although the term ‘slacktivism’ is sometimes used to denote a watered down version of civic engagement and activism that is reduced to clicking a ‘Like’ button and signing online petitions, we believe that we are far from witnessing another Biedermeier period that saw people focus on the domestic and the non-political. There is plenty of evidence to the contrary, such as post-election violence in Kenya in 2008, the Occupy movements in New York, Hong Kong and elsewhere, the Arab Spring, Stuttgart 21, Fukushima, the Taksim Gezi Park in Istanbul, and the Vinegar Movement in Brazil in 2013. These examples of civic action shape the dynamics of governments, and in turn, call for new processes to be incorporated into governance structures. Participatory research into these new processes across the triad of people, place and technology is a significant and timely investment to foster productive, sustainable, and livable human habitats. With this chapter, we want to reframe the current debates in academia and priorities in industry and government to allow citizens and civic actors to take their rightful centerpiece place in civic movements. This calls for new participatory approaches for co-inquiry and co-design. It is an evolving process with an explicit agenda to facilitate change, and we propose participatory action research (PAR) as an indispensable component in the journey to develop new governance infrastructures and practices for civic engagement. This chapter proposes participatory action research as a useful and fitting research paradigm to guide methodological considerations surrounding the study, design, development, and evaluation of civic technologies. We do not limit our definition of civic technologies to tools specifically designed to simply enhance government and governance, such as renewing your car registration online or casting your vote electronically on election day. Rather, we are interested in civic media and technologies that foster citizen engagement in the widest sense, and particularly the participatory design of such civic technologies that strive to involve citizens in political debate and action as well as question conventional approaches to political issues (DiSalvo, 2012; Dourish, 2010; Foth et al., 2013). Following an outline of some underlying principles and assumptions behind participatory action research, especially as it applies to cities, we will critically review case studies to illustrate the application of this approach with a view to engender robust, inclusive, and dynamic societies built on the principles of engaged liberal democracy. The rationale for this approach is an alternative to smart cities in a ‘perpetual tomorrow,’ (cf. e.g. Dourish & Bell, 2011), based on many weak and strong signals of civic actions revolving around technology seen today. It seeks to emphasize and direct attention to active citizenry over passive consumerism, human actors over human factors, culture over infrastructure, and prosperity over efficiency. First, we will have a look at some fundamental issues arising from applying simplistic smart city visions to the kind of a problem a city is (cf. Jacobs, 1961). We focus on the touch points between “the city” and its civic body, the citizens. In order to provide for meaningful civic engagement, the city must provide appropriate interfaces.

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The future of civic engagement is characterised by both technological innovation as well as new technological user practices that are fuelled by trends towards mobile, personal devices; broadband connectivity; open data; urban interfaces; and cloud computing. These technology trends are progressing at a rapid pace, and have led global technology vendors to package and sell the “Smart City” as a centralised service delivery platform predicted to optimise and enhance cities’ key performance indicators – and generate a profitable market. The top-down deployment of these large and proprietary technology platforms have helped sectors such as energy, transport, and healthcare to increase efficiencies. However, an increasing number of scholars and commentators warn of another “IT bubble” emerging. Along with some city leaders, they argue that the top-down approach does not fit the governance dynamics and values of a liberal democracy when applied across sectors. A thorough understanding is required, of the socio-cultural nuances of how people work, live, play across different environments, and how they employ social media and mobile devices to interact with, engage in, and constitute public realms. Although the term “slacktivism” is sometimes used to denote a watered down version of civic engagement and activism that is reduced to clicking a “Like” button and signing online petitions, we believe that we are far from witnessing another Biedermeier period that saw people focus on the domestic and the non-political. There is plenty of evidence to the contrary, such as post-election violence in Kenya in 2008, the Occupy movements in New York, Hong Kong and elsewhere, the Arab Spring, Stuttgart 21, Fukushima, the Taksim Gezi Park in Istanbul, and the Vinegar Movement in Brazil in 2013. These examples of civic action shape the dynamics of governments, and in turn, call for new processes to be incorporated into governance structures. Participatory research into these new processes across the triad of people, place and technology is a significant and timely investment to foster productive, sustainable, and liveable human habitats. With this article, we want to reframe the current debates in academia and priorities in industry and government to allow citizens and civic actors to take their rightful centrepiece place in civic movements. This calls for new participatory approaches for co-inquiry and co-design. It is an evolving process with an explicit agenda to facilitate change, and we propose participatory action research (PAR) as an indispensable component in the journey to develop new governance infrastructures and practices for civic engagement. We do not limit our definition of civic technologies to tools specifically designed to simply enhance government and governance, such as renewing your car registration online or casting your vote electronically on election day. Rather, we are interested in civic media and technologies that foster citizen engagement in the widest sense, and particularly the participatory design of such civic technologies that strive to involve citizens in political debate and action as well as question conventional approaches to political issues. The rationale for this approach is an alternative to smart cities in a “perpetual tomorrow,” based on many weak and strong signals of civic actions revolving around technology seen today. It seeks to emphasise and direct attention to active citizenry over passive consumerism, human actors over human factors, culture over infrastructure, and prosperity over efficiency. First, we will have a look at some fundamental issues arising from applying simplistic smart city visions to the kind of a problem a city poses. We focus on the touch points between “the city” and its civic body, the citizens. In order to provide for meaningful civic engagement, the city must provide appropriate interfaces.

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There are many applications such as software for processing customer records in telecom, patient records in hospitals, email processing software accessing a single email in a mailbox etc. which require to access a single record in a database consisting of millions of records. A basic feature of these applications is that they need to access data sets which are very large but simple. Cloud computing provides computing requirements for these kinds of new generation of applications involving very large data sets which cannot possibly be handled efficiently using traditional computing infrastructure. In this paper, we describe storage services provided by three well-known cloud service providers and give a comparison of their features with a view to characterize storage requirements of very large data sets as examples and we hope that it would act as a catalyst for the design of storage services for very large data set requirements in future. We also give a brief overview of other kinds of storage that have come up in the recent past for cloud computing.

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The mobile cloud computing model promises to address the resource limitations of mobile devices, but effectively implementing this model is difficult. Previous work on mobile cloud computing has required the user to have a continuous, high-quality connection to the cloud infrastructure. This is undesirable and possibly infeasible, as the energy required on the mobile device to maintain a connection, and transfer sizeable amounts of data is large; the bandwidth tends to be quite variable, and low on cellular networks. The cloud deployment itself needs to efficiently allocate scalable resources to the user as well. In this paper, we formulate the best practices for efficiently managing the resources required for the mobile cloud model, namely energy, bandwidth and cloud computing resources. These practices can be realised with our mobile cloud middleware project, featuring the Cloud Personal Assistant (CPA). We compare this with the other approaches in the area, to highlight the importance of minimising the usage of these resources, and therefore ensure successful adoption of the model by end users. Based on results from experiments performed with mobile devices, we develop a no-overhead decision model for task and data offloading to the CPA of a user, which provides efficient management of mobile cloud resources.

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Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.

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Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

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Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

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Demand Side Management (DSM) plays an important role in Smart Grid. It has large scale access points, massive users, heterogeneous infrastructure and dispersive participants. Moreover, cloud computing which is a service model is characterized by resource on-demand, high reliability and large scale integration and so on and the game theory is a useful tool to the dynamic economic phenomena. In this study, a scheme design of cloud + end technology is proposed to solve technical and economic problems of the DSM. The architecture of cloud + end is designed to solve technical problems in the DSM. In particular, a construct model of cloud + end is presented to solve economic problems in the DSM based on game theories. The proposed method is tested on a DSM cloud + end public service system construction in a city of southern China. The results demonstrate the feasibility of these integrated solutions which can provide a reference for the popularization and application of the DSM in china.