44 resultados para cloud computing datacenter performance QoS

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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The increasing dependency of everyday life on mobile devices also increases the number and complexity of computing tasks to be supported by these devices. However, the inherent requirement of mobility restricts them from being resources rich both in terms of energy (battery capacity) and other computing resources such as processing capacity, memory and other resources. This thesis looks into cyber foraging technique of offloading computing tasks. Various experiments on android mobile devices are carried out to evaluate offloading benefits in terms of sustainability advantage, prolonging battery life and augmenting the performance of mobile devices. This thesis considers two scenarios of cyber foraging namely opportunistic offloading and competitive offloading. These results show that the offloading scenarios are important for both green computing and resource augmentation of mobile devices. A significant advantage in battery life gain and performance enhancement is obtained. Moreover, cyber foraging is proved to be efficient in minimizing energy consumption per computing tasks. The work is based on scavenger cyber foraging system. In addition, the work can be used as a basis for studying cyber foraging and other similar approaches such as mobile cloud/edge computing for internet of things devices and improving the user experiences of applications by minimizing latencies through the use of potential nearby surrogates.

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This thesis discusses the opportunities and challenges of the cloud computing technology in healthcare information systems by reviewing the existing literature on cloud computing and healthcare information system and the impact of cloud computing technology to healthcare industry. The review shows that if problems related to security of data are solved then cloud computing will positively transform the healthcare institutions by giving advantage to the healthcare IT infrastructure as well as improving and giving benefit to healthcare services. Therefore, this thesis will explore the opportunities and challenges that are associated with cloud computing in the context of Finland in order to help the healthcare organizations and stakeholders to determine its direction when it decides to adopt cloud technology on their information systems.

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Video transcoding refers to the process of converting a digital video from one format into another format. It is a compute-intensive operation. Therefore, transcoding of a large number of simultaneous video streams requires a large amount of computing resources. Moreover, to handle di erent load conditions in a cost-e cient manner, the video transcoding service should be dynamically scalable. Infrastructure as a Service Clouds currently offer computing resources, such as virtual machines, under the pay-per-use business model. Thus the IaaS Clouds can be leveraged to provide a coste cient, dynamically scalable video transcoding service. To use computing resources e ciently in a cloud computing environment, cost-e cient virtual machine provisioning is required to avoid overutilization and under-utilization of virtual machines. This thesis presents proactive virtual machine resource allocation and de-allocation algorithms for video transcoding in cloud computing. Since users' requests for videos may change at di erent times, a check is required to see if the current computing resources are adequate for the video requests. Therefore, the work on admission control is also provided. In addition to admission control, temporal resolution reduction is used to avoid jitters in a video. Furthermore, in a cloud computing environment such as Amazon EC2, the computing resources are more expensive as compared with the storage resources. Therefore, to avoid repetition of transcoding operations, a transcoded video needs to be stored for a certain time. To store all videos for the same amount of time is also not cost-e cient because popular transcoded videos have high access rate while unpopular transcoded videos are rarely accessed. This thesis provides a cost-e cient computation and storage trade-o strategy, which stores videos in the video repository as long as it is cost-e cient to store them. This thesis also proposes video segmentation strategies for bit rate reduction and spatial resolution reduction video transcoding. The evaluation of proposed strategies is performed using a message passing interface based video transcoder, which uses a coarse-grain parallel processing approach where video is segmented at group of pictures level.

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Smart phones became part and parcel of our life, where mobility provides a freedom of not being bounded by time and space. In addition, number of smartphones produced each year is skyrocketing. However, this also created discrepancies or fragmentation among devices and OSes, which in turn made an exceeding hard for developers to deliver hundreds of similar featured applications with various versions for the market consumption. This thesis is an attempt to investigate whether cloud based mobile development platforms can mitigate and eventually eliminate fragmentation challenges. During this research, we have selected and analyzed the most popular cloud based development platforms and tested integrated cloud features. This research showed that cloud based mobile development platforms may able to reduce mobile fragmentation and enable to utilize single codebase to deliver a mobile application for different platforms.

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Manufacturing industry has been always facing challenge to improve the production efficiency, product quality, innovation ability and struggling to adopt cost-effective manufacturing system. In recent years cloud computing is emerging as one of the major enablers for the manufacturing industry. Combining the emerged cloud computing and other advanced manufacturing technologies such as Internet of Things, service-oriented architecture (SOA), networked manufacturing (NM) and manufacturing grid (MGrid), with existing manufacturing models and enterprise information technologies, a new paradigm called cloud manufacturing is proposed by the recent literature. This study presents concepts and ideas of cloud computing and cloud manufacturing. The concept, architecture, core enabling technologies, and typical characteristics of cloud manufacturing are discussed, as well as the difference and relationship between cloud computing and cloud manufacturing. The research is based on mixed qualitative and quantitative methods, and a case study. The case is a prototype of cloud manufacturing solution, which is software platform cooperated by ATR Soft Oy and SW Company China office. This study tries to understand the practical impacts and challenges that are derived from cloud manufacturing. The main conclusion of this study is that cloud manufacturing is an approach to achieve the transformation from traditional production-oriented manufacturing to next generation service-oriented manufacturing. Many manufacturing enterprises are already using a form of cloud computing in their existing network infrastructure to increase flexibility of its supply chain, reduce resources consumption, the study finds out the shift from cloud computing to cloud manufacturing is feasible. Meanwhile, the study points out the related theory, methodology and application of cloud manufacturing system are far from maturity, it is still an open field where many new technologies need to be studied.

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Cloud computing enables on-demand network access to shared resources (e.g., computation, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort. Cloud computing refers to both the applications delivered as services over the Internet and the hardware and system software in the data centers. Software as a service (SaaS) is part of cloud computing. It is one of the cloud service models. SaaS is software deployed as a hosted service and accessed over the Internet. In SaaS, the consumer uses the provider‘s applications running in the cloud. SaaS separates the possession and ownership of software from its use. The applications can be accessed from any device through a thin client interface. A typical SaaS application is used with a web browser based on monthly pricing. In this thesis, the characteristics of cloud computing and SaaS are presented. Also, a few implementation platforms for SaaS are discussed. Then, four different SaaS implementation cases and one transformation case are deliberated. The pros and cons of SaaS are studied. This is done based on literature references and analysis of the SaaS implementations and the transformation case. The analysis is done both from the customer‘s and service provider‘s point of view. In addition, the pros and cons of on-premises software are listed. The purpose of this thesis is to find when SaaS should be utilized and when it is better to choose a traditional on-premises software. The qualities of SaaS bring many benefits both for the customer as well as the provider. A customer should utilize SaaS when it provides cost savings, ease, and scalability over on-premises software. SaaS is reasonable when the customer does not need tailoring, but he only needs a simple, general-purpose service, and the application supports customer‘s core business. A provider should utilize SaaS when it offers cost savings, scalability, faster development, and wider customer base over on-premises software. It is wise to choose SaaS when the application is cheap, aimed at mass market, needs frequent updating, needs high performance computing, needs storing large amounts of data, or there is some other direct value from the cloud infrastructure.

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The main objective of this master’s thesis is to provide a comprehensive view to cloud computing and SaaS, and analyze how well CADM, a unit of Capgemini Finland Ltd., would fit to the cloud-based SaaS business. Another objective for this thesis is to investigate how public clouds would fit for CADM as a delivery model, if they would provide SaaS applications to their customers. This master’s thesis is executed by investigating characteristics of cloud computing and SaaS especially from application provider point of view. This is done by exploring what kinds of researches and analysis there have been done regarding these two phenomena during past few years. Then CADM’s current business model and operations are analyzed from SaaS’s and public cloud’s perspective. This analyzing part is conducted by using SWOT analysis which is widely used analytical tool when observing company’s strategic position and when figuring out possibilities how to improve company’s operations. The conducted analysis and observations reveals that CADM should pursue SaaS business as it could provide remarkable advantages and strengthen their position in current markets. However, pure SaaS model would not be the optimal solution for CADM because they do not have own product which could be transformed to SaaS model, and they lack of Infrastructure Management ability. Also public cloud would not be the most suitable delivery model for them if providing SaaS services. The main observation of this thesis is that CADM should adopt the SaaS model via Capgemini Immediate offering.

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Diplomityön tarkoituksena on optimoida asiakkaiden sähkölaskun laskeminen hajautetun laskennan avulla. Älykkäiden etäluettavien energiamittareiden tullessa jokaiseen kotitalouteen, energiayhtiöt velvoitetaan laskemaan asiakkaiden sähkölaskut tuntiperusteiseen mittaustietoon perustuen. Kasvava tiedonmäärä lisää myös tarvittavien laskutehtävien määrää. Työssä arvioidaan vaihtoehtoja hajautetun laskennan toteuttamiseksi ja luodaan tarkempi katsaus pilvilaskennan mahdollisuuksiin. Lisäksi ajettiin simulaatioita, joiden avulla arvioitiin rinnakkaislaskennan ja peräkkäislaskennan eroja. Sähkölaskujen oikeinlaskemisen tueksi kehitettiin mittauspuu-algoritmi.

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Millions of enterprises move their applications to a cloud every year. According to Forrester Research “the global cloud computing market will grow from a $40.7 billion in 2011 to $241 billion in 2020”. Due to increased interests and demand broad range of providers and solutions have appeared in the market. It is vital to be able to predict possible problems correctly and to classify and mitigate risks associated with the migration process. The study will show the main criteria that should be taken into consideration while making decision of moving enterprise applications to the cloud and choosing appropriate vendor. The main goal of the research is to identify main problems during the migration to a cloud and propose a solution for their prevention and mitigation of consequences in case of occurrence. The research provides an overview of existing cloud solutions and deployment models for enterprise applications. It identifies decision drivers of an applications migration to a cloud and potential risks and benefits associated with this. Finally, the best practices for the successful enterprise-to-cloud migration based on the case studies analysis are formulated.

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This study aims to open up some typical models of organizational buying behavior. As the cloud computing and cloud services seem to be the today´s hype, the study seeks to further facilitate the understanding of organizational buying behavior regarding cloud services by interviewing a decision maker of this field in the purchaser´s side and also for comparison a cloud service provider´s representative from the vendor´s side.

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Cloud computing is a practically relevant paradigm in computing today. Testing is one of the distinct areas where cloud computing can be applied. This study addressed the applicability of cloud computing for testing within organizational and strategic contexts. The study focused on issues related to the adoption, use and effects of cloudbased testing. The study applied empirical research methods. The data was collected through interviews with practitioners from 30 organizations and was analysed using the grounded theory method. The research process consisted of four phases. The first phase studied the definitions and perceptions related to cloud-based testing. The second phase observed cloud-based testing in real-life practice. The third phase analysed quality in the context of cloud application development. The fourth phase studied the applicability of cloud computing in the gaming industry. The results showed that cloud computing is relevant and applicable for testing and application development, as well as other areas, e.g., game development. The research identified the benefits, challenges, requirements and effects of cloud-based testing; and formulated a roadmap and strategy for adopting cloud-based testing. The study also explored quality issues in cloud application development. As a special case, the research included a study on applicability of cloud computing in game development. The results can be used by companies to enhance the processes for managing cloudbased testing, evaluating practical cloud-based testing work and assessing the appropriateness of cloud-based testing for specific testing needs.

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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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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Context: Web services have been gaining popularity due to the success of service oriented architecture and cloud computing. Web services offer tremendous opportunity for service developers to publish their services and applications over the boundaries of the organization or company. However, to fully exploit these opportunities it is necessary to find efficient discovery mechanism thus, Web services discovering mechanism has attracted a considerable attention in Semantic Web research, however, there have been no literature surveys that systematically map the present research result thus overall impact of these research efforts and level of maturity of their results are still unclear. This thesis aims at providing an overview of the current state of research into Web services discovering mechanism using systematic mapping. The work is based on the papers published 2004 to 2013, and attempts to elaborate various aspects of the analyzed literature including classifying them in terms of the architecture, frameworks and methods used for web services discovery mechanism. Objective: The objective if this work is to summarize the current knowledge that is available as regards to Web service discovery mechanisms as well as to systematically identify and analyze the current published research works in order to identify different approaches presented. Method: A systematic mapping study has been employed to assess the various Web Services discovery approaches presented in the literature. Systematic mapping studies are useful for categorizing and summarizing the level of maturity research area. Results: The result indicates that there are numerous approaches that are consistently being researched and published in this field. In terms of where these researches are published, conferences are major contributing publishing arena as 48% of the selected papers were conference published papers illustrating the level of maturity of the research topic. Additionally selected 52 papers are categorized into two broad segments namely functional and non-functional based approaches taking into consideration architectural aspects and information retrieval approaches, semantic matching, syntactic matching, behavior based matching as well as QOS and other constraints.