804 resultados para Cloud Computing, Software-as-a-Service (SaaS), SaaS Multi-Tenant, Windows Azure
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Cloud computing, despite its success and promises, presents issues for businesses migrating their legacy applications to cloud. In this research legacy-to-cloud migration issues are reviewed based on literature findings and an experience report. Solutions are applied to Tieto Open Application Suite (TOAS) software development platform running on cloud infrastructure. It is observed that the migration strategy heavily affects the migration approach. For TOAS a strategy of redesigning the applications for cloud is suggested. Common migration-driven application level modifications include adaptation to service-oriented architecture, load balancing, and runtime and technology changes. A cloud platform such as TOAS might introduce additional needs. Decision making on migration strategy is found to be an issue to be solved case by case. Use of assistive decision making tools is suggested.
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The purpose of this study was to find out how a software company can successfully expand business to the Danish software market through distribution channel. The study was commissioned by a Finnish software company and it was conducted using a qualitative research method by analyzing external and internal business environment, and interviewing Danish ICT organizations and M-Files personnel. Interviews were semi-structured interviews, which were designed to collect comprehensive information on the existing ICT and software market in Denmark. The research used three external and internal analyzing frameworks; PEST analysis (market level), Porter´s Five Force analysis (industry level competition) and SWOT analysis (company level). Distribution channels theory was a base to understand why and what kind of distribution channels the case company uses, and what kind of channels target markets companies’ uses. Channel strategy and design were integrated to the industry level analysis. The empirical findings revealed that Denmark has very business friendly ICT environment. Several organizations have ranked Denmark´s information and communication technology as the best in the world. Denmark’s ICT and software market are relatively small, compared to many other countries in Europe. Danish software market is centralized. Largest software clusters are in the largest cities; Copenhagen, Aarhus, Odense and Aalborg. From these clusters, software companies can most likely find suitable resellers. The following growing trends are clearly seen in the software market: mobile and wireless applications, outsourcing, security solutions, cloud computing, social business solutions and e-business solutions. When expanding software business to the Danish market, it is important to take into account these trends. In Denmark distribution channels varies depending on the product or service. For many, a natural distribution channel is a local partner or internet. In the public sector solutions are purchased through a public procurement process. In the private sector the buying process is more straight forwarded. Danish companies are buying software from reliable suppliers. This means that they usually buy software direct from big software vendors or local partners. Some customers prefer to use professional consulting companies. These consulting companies can strongly influence on the selection of the supplier and products, and in this light, consulting companies can be important partners for software companies. Even though the competition is fierce in ECM and DMS solutions, Danish market offers opportunities for foreign companies. Penetration to the Danish market through reseller channel requires advanced solutions and objective selection criteria for channel partners. Based on the findings, Danish companies are interested in advanced and efficient software solutions. Interest towards M-Files solutions was clearly seen and the company has excellent opportunity to expand business to the Danish market through reseller channel. Since the research explored the Danish ICT and software market, the results of the study may offer valuable information also to the other software companies which are expanding their business to the Danish market.
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Nel primo capitolo si è studiata la nuova tecnologia del Cloud Computing, fornendo una semplice analisi di tutte le caratteristiche principali, gli attori coinvolti e i relativi metodi di distribuzione e servizi offerti. Nel secondo capitolo si è introdotta la nozione di coordination as a service, discutendone le relative astrazioni che compongono l'architettura logica. Successivamente si è preso in considerazione il modello di coordinazione TuCSoN definendo cosa si intende per nodo, agente, centro di tuple e agent coordination context ed è stato analizzato il relativo linguaggio di coordinazione attraverso il quale essi interagiscono. Nel terzo capitolo sono state riviste ed estese le nozioni di TuCSoN, precedentemente acquisite, nell'ambito del Cloud Computing ed è stato fornito un modello astratto ed una possibile architettura di TuCSoN in the Cloud. Sono stati analizzati anche gli aspetti di un possibile servizio di tale genere nello scenario di servizio pay-per-use. Infine nel quarto ed ultimo capitolo si è sviluppato un caso di studio in cui si è implementata un'interfaccia per l'attuale CLI di TuCSoN sottoforma di applet, che è stata poi inserita nel Cloud attraverso la piattaforma PaaS Cloudify.
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Questo documento si interroga sulle nuove possibilità offerte agli operatori del mondo delle Reti di Telecomunicazioni dai paradigmi di Network Functions Virtualization, Cloud Computing e Software Defined Networking: questi sono nuovi approcci che permettono la creazione di reti dinamiche e altamente programmabili, senza disdegnare troppo il lato prestazionale. L'intento finale è valutare se con un approccio di questo genere si possano implementare dinamicamente delle concatenazioni di servizi di rete e se le prestazioni finali rispecchiano ciò che viene teorizzato dai suddetti paradigmi. Tutto ciò viene valutato per cercare una soluzione efficace al problema dell'ossificazione di Internet: infatti le applicazioni di rete, dette middle-boxes, comportano costi elevati, situazioni di dipendenza dal vendor e staticità delle reti stesse, portando all'impossibilità per i providers di sviluppare nuovi servizi. Il caso di studio si basa proprio su una rete che implementa questi nuovi paradigmi: si farà infatti riferimento a due diverse topologie, una relativa al Livello L2 del modello OSI (cioè lo strato di collegamento) e una al Livello L3 (strato di rete). Le misure effettuate infine mostrano come le potenzialità teorizzate siano decisamente interessanti e innovative, aprendo un ventaglio di infinite possibilità per il futuro sviluppo di questo settore.
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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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Cloud computing has seen an impressive growth in recent years, with virtualization technologies being massively adopted to create IaaS (Infrastructure as a Service) public and private solutions. Today, the interest is shifting towards the PaaS (Platform as a Service) model, which allows developers to abstract from the execution platform and focus only on the functionality. There are several public PaaS offerings available, but currently no private PaaS solution is ready for production environments. To fill this gap a new solution must be developed. In this paper we present a key element for enabling this model: a cloud repository based on the OSGi component model. The repository stores, manages, provisions and resolves the dependencies of PaaS software components and services. This repository can federate with other repositories located in the same or different clouds, both private and public. This way, dependencies can be fulfilled collaboratively, and new business models can be implemented.
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New technologies such as, the new Information and Communication Technology ICT, break new paths and redefines the way we understand business, the Cloud Computing is one of them. The on demand resource gathering and the per usage payment scheme are now commonplace, and allows companies to save on their ICT investments. Despite the importance of this issue, we still lack methodologies that help companies, to develop applications oriented for its exploitation in the Cloud. In this study we aim to fill this gap and propose a methodology for the development of ICT applications, which are directed towards a business model, and further outsourcing in the Cloud. In the former the Development of SOA applications, we take, as a baseline scenario, a business model from which to obtain a business process model. To this end, we use software engineering tools; and in the latter The Outsourcing we propose a guide that would facilitate uploading business models into the Cloud; to this end we describe a SOA governance model, which controls the SOA. Additionally we propose a Cloud government that integrates Service Level Agreements SLAs, plus SOA governance, and Cloud architecture. Finally we apply our methodology in an example illustrating our proposal. We believe that our proposal can be used as a guide/pattern for the development of business applications.
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We present the results of a study that collected, compared and analyzed the terms and conditions of a number of cloud services vis-a-vis privacy and data protection. First, we assembled a list of factors that comprehensively capture cloud companies' treatment of user data with regard to privacy and data protection; then, we assessed how various cloud services of different types protect their users in the collection, retention, and use of their data, as well as in the disclosure to law enforcement authorities. This commentary provides comparative and aggregate analysis of the results.
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Cloud computing is a new technological paradigm offering computing infrastructure, software and platforms as a pay-as-you-go, subscription-based service. Many potential customers of cloud services require essential cost assessments to be undertaken before transitioning to the cloud. Current assessment techniques are imprecise as they rely on simplified specifications of resource requirements that fail to account for probabilistic variations in usage. In this paper, we address these problems and propose a new probabilistic pattern modelling (PPM) approach to cloud costing and resource usage verification. Our approach is based on a concise expression of probabilistic resource usage patterns translated to Markov decision processes (MDPs). Key costing and usage queries are identified and expressed in a probabilistic variant of temporal logic and calculated to a high degree of precision using quantitative verification techniques. The PPM cost assessment approach has been implemented as a Java library and validated with a case study and scalability experiments. © 2012 Springer-Verlag Berlin Heidelberg.
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Multi-Cloud Applications are composed of services offered by multiple cloud platforms where the user/developer has full knowledge of the use of such platforms. The use of multiple cloud platforms avoids the following problems: (i) vendor lock-in, which is dependency on the application of a certain cloud platform, which is prejudicial in the case of degradation or failure of platform services, or even price increasing on service usage; (ii) degradation or failure of the application due to fluctuations in quality of service (QoS) provided by some cloud platform, or even due to a failure of any service. In multi-cloud scenario is possible to change a service in failure or with QoS problems for an equivalent of another cloud platform. So that an application can adopt the perspective multi-cloud is necessary to create mechanisms that are able to select which cloud services/platforms should be used in accordance with the requirements determined by the programmer/user. In this context, the major challenges in terms of development of such applications include questions such as: (i) the choice of which underlying services and cloud computing platforms should be used based on the defined user requirements in terms of functionality and quality (ii) the need to continually monitor the dynamic information (such as response time, availability, price, availability), related to cloud services, in addition to the wide variety of services, and (iii) the need to adapt the application if QoS violations affect user defined requirements. This PhD thesis proposes an approach for dynamic adaptation of multi-cloud applications to be applied when a service is unavailable or when the requirements set by the user/developer point out that other available multi-cloud configuration meets more efficiently. Thus, this work proposes a strategy composed of two phases. The first phase consists of the application modeling, exploring the similarities representation capacity and variability proposals in the context of the paradigm of Software Product Lines (SPL). In this phase it is used an extended feature model to specify the cloud service configuration to be used by the application (similarities) and the different possible providers for each service (variability). Furthermore, the non-functional requirements associated with cloud services are specified by properties in this model by describing dynamic information about these services. The second phase consists of an autonomic process based on MAPE-K control loop, which is responsible for selecting, optimally, a multicloud configuration that meets the established requirements, and perform the adaptation. The adaptation strategy proposed is independent of the used programming technique for performing the adaptation. In this work we implement the adaptation strategy using various programming techniques such as aspect-oriented programming, context-oriented programming and components and services oriented programming. Based on the proposed steps, we tried to assess the following: (i) the process of modeling and the specification of non-functional requirements can ensure effective monitoring of user satisfaction; (ii) if the optimal selection process presents significant gains compared to sequential approach; and (iii) which techniques have the best trade-off when compared efforts to development/modularity and performance.
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Postprint
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Simulating the efficiency of business processes could reveal crucial bottlenecks for manufacturing companies and could lead to significant optimizations resulting in decreased time to market, more efficient resource utilization, and larger profit. While such business optimization software is widely utilized by larger companies, SMEs typically do not have the required expertise and resources to efficiently exploit these advantages. The aim of this work is to explore how simulation software vendors and consultancies can extend their portfolio to SMEs by providing business process optimization based on a cloud computing platform. By executing simulation runs on the cloud, software vendors and associated business consultancies can get access to large computing power and data storage capacity on demand, run large simulation scenarios on behalf of their clients, analyze simulation results, and advise their clients regarding process optimization. The solution is mutually beneficial for both vendor/consultant and the end-user SME. End-user companies will only pay for the service without requiring large upfront costs for software licenses and expensive hardware. Software vendors can extend their business towards the SME market with potentially huge benefits.
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We present Dithen, a novel computation-as-a-service (CaaS) cloud platform specifically tailored to the parallel ex-ecution of large-scale multimedia tasks. Dithen handles the upload/download of both multimedia data and executable items, the assignment of compute units to multimedia workloads, and the reactive control of the available compute units to minimize the cloud infrastructure cost under deadline-abiding execution. Dithen combines three key properties: (i) the reactive assignment of individual multimedia tasks to available computing units according to availability and predetermined time-to-completion constraints; (ii) optimal resource estimation based on Kalman-filter estimates; (iii) the use of additive increase multiplicative decrease (AIMD) algorithms (famous for being the resource management in the transport control protocol) for the control of the number of units servicing workloads. The deployment of Dithen over Amazon EC2 spot instances is shown to be capable of processing more than 80,000 video transcoding, face detection and image processing tasks (equivalent to the processing of more than 116 GB of compressed data) for less than $1 in billing cost from EC2. Moreover, the proposed AIMD-based control mechanism, in conjunction with the Kalman estimates, is shown to provide for more than 27% reduction in EC2 spot instance cost against methods based on reactive resource estimation. Finally, Dithen is shown to offer a 38% to 500% reduction of the billing cost against the current state-of-the-art in CaaS platforms on Amazon EC2 (Amazon Lambda and Amazon Autoscale). A baseline version of Dithen is currently available at dithen.com.
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117 p.
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The current infrastructure as a service (IaaS) cloud systems, allow users to load their own virtual machines. However, most of these systems do not provide users with an automatic mechanism to load a network topology of virtual machines. In order to specify and implement the network topology, we use software switches and routers as network elements. Before running a group of virtual machines, the user needs to set up the system once to specify a network topology of virtual machines. Then, given the user’s request for running a specific topology, our system loads the appropriate virtual machines (VMs) and also runs separated VMs as software switches and routers. Furthermore, we have developed a manager that handles physical hardware failure situations. This system has been designed in order to allow users to use the system without knowing all the internal technical details.