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Автор: Grafiati
Опубліковано: 6 вересня 2023

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Статті в журналах з теми "Cloud computing platform"

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Zhange, Zhi, Liwei Wang, Ruiying Liu, and Jinghang Fan. "Development of Cloud Computing Platform Based on Neural Network." Mathematical Problems in Engineering 2022 (March 7, 2022): 1–9. http://dx.doi.org/10.1155/2022/1513081.

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Aiming at the problems of small data storage, small platform throughput, and high energy consumption in the development of existing cloud computing platforms, this paper develops a cloud computing platform based on neural networks. In the design of the platform, firstly, the functions of the cloud computing platform are determined. Based on the function design, the hardware and software of the cloud computing platform are designed. In the hardware design, the topology of cloud computing platform, data acquisition module, single-chip microcomputer, node deployment, and other types of functional hardware are designed. In the software design, the neural network is mainly used to remove the redundancy of data stored in a cloud computing platform, design the data processing flow of cloud computing platform, and complete the development of cloud computing platform based on neural network. The experimental results show that the cloud computing platform based on the neural network designed in this paper runs faster, the throughput of platform data has been significantly improved, and the operating energy consumption of the platform is low.
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2

Zhiyuan, Fang, and Wei Li. "Cloud Service Platform." International Journal of Information Systems in the Service Sector 5, no. 3 (July 2013): 54–62. http://dx.doi.org/10.4018/jisss.2013070104.

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Health Information eXchange (HIX) is a part of Happiness Cloud Service Platform of Happiness Guangdong in Guangdong Province of China based on innovation of cloud-based business model. This article illustrates the hospital health care business services system based on cloud computing. major business functions of HIX includes integrated mobile medical information services, and mobile health information services. Key cloud service platform capabilities include appointment of HIX registration, doctor-patient interaction and Health Manager System, medical statistical analysis, and the other integrated support module including service platform and platform management provided by two major cloud computing technologies of SaaS and PaaS. Medical cloud services of HIX is an innovative business model for cloud computing, that is, the medical and health services provided to the public going though by cloud computing all over Guangdong Province in China.
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M, Govindaraj. "Computing Waste Management Using Cloud Platform and Sensors." International Journal of Psychosocial Rehabilitation 24, no. 5 (May 25, 2020): 6987–91. http://dx.doi.org/10.37200/ijpr/v24i5/pr2020700.

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4

Chauhan, Akash. "A Comparative Study of Cloud Computing Platforms." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 11, no. 1 (April 30, 2020): 821–26. http://dx.doi.org/10.17762/turcomat.v11i1.13563.

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Анотація:
This article offers a comparison and analysis of three of the most widely used cloud computing platforms: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). The research focuses on the most important aspects of each platform, such as the virtual machines they offer, the storage choices they provide, the database services they provide, and the serverless computing capabilities they provide. In addition to this, the paper discusses issues like as cost, availability, security, and scalability, as well as some of the positives and negatives associated with using each platform. The literature review that is included in this paper highlights some of the most important findings from recent studies on cloud computing platforms. These findings include the widespread use of Amazon Web Services (AWS), the difficulties that are encountered by organisations in the management of cloud computing resources, and the significance of aspects such as reliability, security, and cost when selecting a cloud computing platform. This article's overarching objective is to offer businesses a comprehensive introduction to AWS, Microsoft Azure, and Google Cloud Platform (GCP), and to assist those businesses in making well-informed choices regarding which cloud platform is best suited to meet their requirements.
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5

He, Dan Dan, Fang Qin, and Can Wang. "Application of Cloud Counting in Product Platform Design Services Research." Applied Mechanics and Materials 513-517 (February 2014): 1765–68. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1765.

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Анотація:
Product platform is a key theory in mass customization method, and it can satisfy diversely customer needs at high efficiency service and reduce enterprise product development costs. This dissertation explores the product platform development routing and design ability service and resources virtualization and other key technologies in the migration process of product platform to cloud platform in the background of computing clouds technology and product platform theory. It proposes the product platform design service architecture based on cloud computing and its design service modes and the related key technology to the study, including product platform resources virtualization in cloud computing environment and product family design ability services technology and product platform cloud data center retrieval technology, etc.
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Liu, Ji. "Optimization and Management in Order to Drive Targeted Networking Memory Database." Applied Mechanics and Materials 727-728 (January 2015): 965–68. http://dx.doi.org/10.4028/www.scientific.net/amm.727-728.965.

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Анотація:
In today's vehicle networking system architecture is mainly composed of four parts: sensor networks, wireless communication networks, cloud computing platforms and vehicle terminal. Wireless sensor network is responsible for the front of the real-time collection of traffic information, a wireless communication network to send information to the backend of the cloud computing platform, cloud computing platform to handle a large number of vehicles to collect real-time information from the front, and finally sends the information to the end user. In this thesis, this car networking research background, analyze vehicle networking system architecture consisting of performance indicators for each part of the system recognize cloud platform for large data processing efficiency as well as room for improvement. Then put forward the traditional computing platform I / O disk database with in-memory database to replace the cloud to enhance cloud computing platform for large data processing efficiency.
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Cheng, Peng, and Hui Qu. "Design and Realization Based on Cloud Stack Hybrid Cloud Computing Platform." Advanced Materials Research 989-994 (July 2014): 2297–300. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2297.

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While setting up the cloud computing platform by using OpenStack, there were some disadvantages such as very tedious operating steps and low efficiency. In this paper, we put forward a design and realization method based on CloudStack hybrid cloud computing platform. Firstly, we used CloudStack as tool to set up two independent cloud platforms, one of them was called public cloud and the other one private cloud. Then virtualization technology and a shared resource classification method discussed in this paper were performed to set up two virtual sub-servers on the main server and operate the cloud platform already established on it. Finally, we gave the two platforms corresponding authority, thus the hybrid cloud platform was established. This method was easy to set up and could reduce the cost effectively, therefore, it was very practical.
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Qaisar, Faizan, Hammad Shahab, Muhammad Iqbal, Hussain Mahmood Sargana, Muhammad Aqeel, and Muhammad Arslan Qayyum. "Recent Trends in Cloud Computing and IoT Platforms for IT Management and Development: A Review." Pakistan Journal of Engineering and Technology 6, no. 1 (March 10, 2023): 98–105. http://dx.doi.org/10.51846/vol6iss1pp98-105.

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Анотація:
Cloud computing has transformed the delivery and management of IT services, and with the advent of the Internet of Things (IoT), cloud platforms have become even more crucial for developing and managing IT solutions. This critical review article presents the latest research on cloud computing platforms with IoT capability and their impact on IT management and development. The review covers the advantages of cloud computing platforms, including their cost-effectiveness, scalability, and flexibility. It also provides an in-depth analysis of six leading cloud platforms with IoT capability: ThingSpeak, Ubidots Platform, AWS IoT, IBM Watson, ThingWorx, and Salesforce Platform. The review focuses on their features, capabilities, and limitations. The article concludes by emphasizing the crucial role of cloud computing platforms with IoT capability in IT management and development and their potential for future growth and development. The insights provided by this review are essential for researchers and practitioners who seek to comprehend the emerging trends in cloud computing platforms and their impact on IT management and development.
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Li, Ran, Jian Hua Fan, and Xiao Bo Wang. "Technique of Constructing Cloud Computing Platform Based on Ubuntu Enterprise Cloud." Advanced Materials Research 482-484 (February 2012): 713–16. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.713.

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Анотація:
Cloud computing is an effective approach for organizing computing resource and improving computing capability. In this paper, we designed and contstucted a private cloud computing platform based on ubuntu enterprise cloud. The cloud computing platform supports various clients dynamicly connet to cloud server and get cloud computing service via interface platform provided. Various kinds of virtual machine instance of different settings running on physical servers provide users computing and storage capability on demand. A series of high level functions guarantee computing service provision of platform.
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Khalifa, Iraky, Hala El-Sayed, and Islam Abd El-Gaber. "Enhanced Mobile Cloud Computing Platform." International Journal of Computer Applications 63, no. 7 (February 15, 2013): 12–18. http://dx.doi.org/10.5120/10477-5209.

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Дисертації з теми "Cloud computing platform"

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Khalifa, Ahmed Abdelmonem Abuelfotooh Ali. "Collaborative Computing Cloud: Architecture and Management Platform." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/72866.

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Анотація:
We are witnessing exponential growth in the number of powerful, multiply-connected, energy-rich stationary and mobile nodes, which will make available a massive pool of computing and communication resources. We claim that cloud computing can provide resilient on-demand computing, and more effective and efficient utilization of potentially infinite array of resources. Current cloud computing systems are primarily built using stationary resources. Recently, principles of cloud computing have been extended to the mobile computing domain aiming to form local clouds using mobile devices sharing their computing resources to run cloud-based services. However, current cloud computing systems by and large fail to provide true on-demand computing due to their lack of the following capabilities: 1) providing resilience and autonomous adaptation to the real-time variation of the underlying dynamic and scattered resources as they join or leave the formed cloud; 2) decoupling cloud management from resource management, and hiding the heterogeneous resource capabilities of participant nodes; and 3) ensuring reputable resource providers and preserving the privacy and security constraints of these providers while allowing multiple users to share their resources. Consequently, systems and consumers are hindered from effectively and efficiently utilizing the virtually infinite pool of computing resources. We propose a platform for mobile cloud computing that integrates: 1) a dynamic real-time resource scheduling, tracking, and forecasting mechanism; 2) an autonomous resource management system; and 3) a cloud management capability for cloud services that hides the heterogeneity, dynamicity, and geographical diversity concerns from the cloud operation. We hypothesize that this would enable 'Collaborative Computing Cloud (C3)' for on-demand computing, which is a dynamically formed cloud of stationary and/or mobile resources to provide ubiquitous computing on-demand. The C3 would support a new resource-infinite computing paradigm to expand problem solving beyond the confines of walled-in resources and services by utilizing the massive pool of computing resources, in both stationary and mobile nodes. In this dissertation, we present a C3 management platform, named PlanetCloud, for enabling both a new resource-infinite computing paradigm using cloud computing over stationary and mobile nodes, and a true ubiquitous on-demand cloud computing. This has the potential to liberate cloud users from being concerned about resource constraints and provides access to cloud anytime and anywhere. PlanetCloud synergistically manages 1) resources to include resource harvesting, forecasting and selection, and 2) cloud services concerned with resilient cloud services to include resource provider collaboration, application execution isolation from resource layer concerns, seamless load migration, fault-tolerance, the task deployment, migration, revocation, etc. Specifically, our main contributions in the context of PlanetCloud are as follows. 1. PlanetCloud Resource Management • Global Resource Positioning System (GRPS): Global mobile and stationary resource discovery and monitoring. A novel distributed spatiotemporal resource calendaring mechanism with real-time synchronization is proposed to mitigate the effect of failures occurring due to unstable connectivity and availability in the dynamic mobile environment, as well as the poor utilization of resources. This mechanism provides a dynamic real-time scheduling and tracking of idle mobile and stationary resources. This would enhance resource discovery and status tracking to provide access to the right-sized cloud resources anytime and anywhere. • Collaborative Autonomic Resource Management System (CARMS): Efficient use of idle mobile resources. Our platform allows sharing of resources, among stationary and mobile devices, which enables cloud computing systems to offer much higher utilization, resulting in higher efficiency. CARMS provides system-managed cloud services such as configuration, adaptation and resilience through collaborative autonomic management of dynamic cloud resources and membership. This helps in eliminating the limited self and situation awareness and collaboration of the idle mobile resources. 2. PlanetCloud Cloud Management Architecture for resilient cloud operation on dynamic mobile resources to provide stable cloud in a continuously changing operational environment. This is achieved by using trustworthy fine-grained virtualization and task management layer, which isolates the running application from the underlying physical resource enabling seamless execution over heterogeneous stationary and mobile resources. This prevents the service disruption due to variable resource availability. The virtualization and task management layer comprises a set of distributed powerful nodes that collaborate autonomously with resource providers to manage the virtualized application partitions.
Ph. D.
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2

Bhattacharjee, Ratnadeep. "An analysis of the cloud computing platform." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/47864.

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Анотація:
Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2009.
Includes bibliographical references.
A slew of articles have been written about the fact that computing will eventually go in the direction of electricity. Just as most software users these days also own the hardware that runs the software, electricity users in the days of yore used to generate their own power. However, over time with standardization in voltage and frequency of generated power and better distribution mechanisms the generation of electricity was consolidated amongst fewer utility providers. The same is being forecast for computing infrastructure. Its is being touted that more and more users will rent computing infrastructure from a utility or "cloud" provider instead of maintaining their own hardware. This phenomenon or technology is being referred to Cloud Computing or Utility Computing. Cloud computing has been in existence in some form or the other since the beginning of computing. However, the advent of vastly improved software, hardware and communication technologies has given special meaning to the term cloud computing and opened up a world of possibilities. It is possible today to start an ecommerce or related company without investing in datacenters. This has turned out to be very beneficial to startups and smaller companies that want to test the efficacy of their idea before making any investment in expensive hardware. Corporations like Amazon, SalesForce.com, Google, IBM, Sun Microsystems, and many more are offering or planning to offer these infrastructure services in one form or another.
(cont.) An ecosystem has already been created and going by the investment and enthusiasm in this space the ecosystem is bound to grow. This thesis tries to define and explain the fundamentals of cloud computing. It looks at the technical aspects of this industry and the kind of applications where cloud can be used. It also looks at the economic value created by the platform, the network externalities, its effect on traditional software companies and their reaction to this technology. The thesis also tries to apply the principle of multi-homing, coring and tipping to the cloud-computing platform and explain the results. The hurdles for both users and providers of this service are also examined in this thesis.
by Ratnadeep Bhattacharjee.
S.M.
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Siddiqui, Muhammad Anas. "Cloud Computing : Evaluation, as a platform for Scania Architecture." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-18896.

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Анотація:
Cloud computing has been given a great deal of attention during recent years. Almost all the technology market leaders and leading hosting service providers (like IBM, Microsoft and Verizon) have entered into the Cloud market as Cloud Providers. Cloud computing promises to provide highly available, secure, low cost, agile and highly scalable solution to the consumers. Scania is a global company and one of the world’s leading heavy vehicle manufacturers with 35,000+ employees. All the large organizations such as Scania, aim to constantly update themselves with the latest technology in order to meet their business requirements but, these organizations must always be convinced that there is a strong reason(s) to implement new technology. This research provides the method and criteria in relation to initiating Cloud computing. A number of Scania’s specific business requirements that it is possible to map to the Cloud are addressed in this thesis. The methodology of research is split in two parts. Firstly, the identification of business cases at Scania and their requirements with the Cloud and Secondly, the evaluation and comparison of the functionalities and capabilities of different vendors. The accumulated data is then compared and suitable vendors, according to those business requirements are suggested. This thesis also shares the experience of moving on premise applications to the Cloud. These are Scania specific applications which are currently being hosted in-house. The research also addresses the possibilities of portability between the Cloud providers. Although there is no standardization in relation to Cloud computing, some initiatives such as OpenStack are available and its current position and some application and data migration tools are also discussed. The thesis concludes with a general discussion, recommendations in relation to adapting Cloud computing and selecting the Cloud provider. This recommendation applies to every organization including Scania.
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Margaris, Nikos. "Cloud Computing v českém prostředí." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-72541.

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Анотація:
Focus of this diploma thesis is on Cloud Computing -- a new delivery model of IS/ICT services for companies. Cloud Computing services are IT resources available to users via internet on pay-as-you-use basis. The aim of the thesis is define underlying Cloud Computing concepts and evaluate the current state of Cloud Computing adoption in the Czech Republic. We discuss the framework for definition of Cloud Computing concepts in the theoretical part of the thesis drawing on resources available in the literature. Cloud Computing survey is conducted using an online questionnaire and followsthe principles established in theoretical part. The main contribution of this thesis is creating working definition of Cloud Computing and identifying reasons that affect adoption rate in the Czech Republic.
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Susani, Nahid. "On Open Platform for Multi-Access Edge Computing." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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Анотація:
The Idea of moving the functions of centralized cloud computing to the edge devices of the network, brought several advantages such as low latency, higher spectral efficiency, supporting machine to machine communication. The idea of decoupling network function from infrastructure well applied for this revolution. Therefor, the concept of software defined network (SDN) and network function virtualization considered as emerging solutions for the future network. With applying NFV in the edge devices, computing services and also using network functions would be possible through using virtual machines provided by NFV. In the first chapter, there are introductions of cloud, Edge cloud computing and SDN/NFV due to the importance of these topics. Containerization of application is an another proposed concept as lightweight virtualization solution which besides NFV can be proper solution for delivering, implementing and running application in the edge network and using advantages. In fact, developer encapsulate applications inside of the containers and containerization will allows to delivery applications across different environments. In second chapter, centralized cloud and Edge Cloud had been explained and it had been moved to introducing kubernetes as Edge cloud orchestrator in third chapter. In this project, Kubernetes has been used as an open source platform for multi access edge computing which works as container cluster orchestrator. Forth chapter has been dedicated to Implementation and Evaluation of the work. Main targets of this real implementation will be extending platform of container cluster from single platform architecture to multi-platform architecture made by different physical infrastructure of AMD64 on Intel and ARM on Raspberry pi using docker containers. The second target of implementation is checking the feasibility of autoscalling number of pods based on CPU utilization of pods, across nodes with heterogeneous platform inside the same cluster.
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Agarwal, Dinesh. "Scientific High Performance Computing (HPC) Applications On The Azure Cloud Platform." Digital Archive @ GSU, 2013. http://digitalarchive.gsu.edu/cs_diss/75.

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Cloud computing is emerging as a promising platform for compute and data intensive scientific applications. Thanks to the on-demand elastic provisioning capabilities, cloud computing has instigated curiosity among researchers from a wide range of disciplines. However, even though many vendors have rolled out their commercial cloud infrastructures, the service offerings are usually only best-effort based without any performance guarantees. Utilization of these resources will be questionable if it can not meet the performance expectations of deployed applications. Additionally, the lack of the familiar development tools hamper the productivity of eScience developers to write robust scientific high performance computing (HPC) applications. There are no standard frameworks that are currently supported by any large set of vendors offering cloud computing services. Consequently, the application portability among different cloud platforms for scientific applications is hard. Among all clouds, the emerging Azure cloud from Microsoft in particular remains a challenge for HPC program development both due to lack of its support for traditional parallel programming support such as Message Passing Interface (MPI) and map-reduce and due to its evolving application programming interfaces (APIs). We have designed newer frameworks and runtime environments to help HPC application developers by providing them with easy to use tools similar to those known from traditional parallel and distributed computing environment set- ting, such as MPI, for scientific application development on the Azure cloud platform. It is challenging to create an efficient framework for any cloud platform, including the Windows Azure platform, as they are mostly offered to users as a black-box with a set of application programming interfaces (APIs) to access various service components. The primary contributions of this Ph.D. thesis are (i) creating a generic framework for bag-of-tasks HPC applications to serve as the basic building block for application development on the Azure cloud platform, (ii) creating a set of APIs for HPC application development over the Azure cloud platform, which is similar to message passing interface (MPI) from traditional parallel and distributed setting, and (iii) implementing Crayons using the proposed APIs as the first end-to-end parallel scientific application to parallelize the fundamental GIS operations.
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7

NASSER, RAFAEL BARBOSA. "A CLOUD COMPUTING PLATFORM FOR STORING GEOREFERENCED MOBILITY DATA." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28415@1.

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Анотація:
PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE EXCELENCIA ACADEMICA
A qualidade de vida nos grandes centros urbanos tem sido motivo de preocupação para governantes, empresários e para a população residente em geral. Os serviços de transporte público coletivo exercem papel central nessa discussão, uma vez que determinam, sobretudo para aquela camada da sociedade de menor poder aquisitivo, o tempo desperdiçado diariamente em seus deslocamentos. Nas metrópoles brasileiras, os ônibus municipais são predominantes no transporte coletivo. Os usuários deste serviço – passageiros – não dispõem de informações atualizadas sobre os ônibus e linhas de ônibus em operação. Oferecer essa natureza de informação contribui para uma melhor experiência de uso diário deste modal e, consequentemente, proporciona maior qualidade de vida aos seus usuários. Em uma visão mais abrangente, os ônibus podem ser considerados sensores que viabilizam a compreensão dos padrões e identificação de anomalias no tráfego de veículos nas áreas urbanas, possibilitando galgar benefícios para toda população. O presente trabalho apresenta uma plataforma na nuvem que captura, enriquece, armazena e disponibiliza os dados dos dispositivos de GPS instalados nos ônibus, permitindo a extração de conhecimento a partir deste valioso e volumoso conjunto de informações. Experimentos são realizados com os ônibus do Município do Rio de Janeiro, com aplicações focadas no passageiro e na sociedade. As metodologias, discussões e técnicas empregadas ao longo do trabalho poderão ser reutilizados para diferentes cidades, modais e perspectivas.
The quality of life in urban centers has been a concern for governments, business and the resident population in general. Public transportation services perform a central role in this discussion, since they determine, especially for that layer of lower-income society, the time wasted daily in their movements. In Brazilian cities, city buses are predominant in public transportion. Users of this service - passengers - do not have updated information of buses and lines. Offer this kind of information contributes to a better everyday experience of this modal and therefore provides greater quality of life for its users. In a broader view, the bus can be considered sensors that enable the understanding of the patterns and identify anomalies in vehicle traffic in urban areas, allowing benefits for the whole population. This work presents a platform in the cloud computing environment that captures, enriches, stores and makes available the data from GPS devices installed on buses, allowing the extraction of knowledge from this valuable and voluminous set of information. Experiments are performed with the buses of the Municipality of Rio de Janeiro, with applications focused on passenger and society. The methodologies, discussions and techniques used throughout the work can be reused for different cities, modal and perspectives.
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Fouodji, Tasse Ghislain. "μCloud : a P2P cloud platform for computing service provision". Thesis, Rhodes University, 2012. http://hdl.handle.net/10962/d1006669.

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Анотація:
The advancements in virtualization technologies have provided a large spectrum of computational approaches. Dedicated computations can be run on private environments (virtual machines), created within the same computer. Through capable APIs, this functionality is leveraged for the service we wish to implement; a computer power service (CPS). We target peer-to-peer systems for this service, to exploit the potential of aggregating computing resources. The concept of a P2P network is mostly known for its expanded usage in distributed networks for sharing resources like content files or real-time data. This study adds computing power to the list of shared resources by describing a suitable service composition. Taking into account the dynamic nature of the platform, this CPS provision is achieved using a self stabilizing clustering algorithm. So, the resulting system of our research is based around a hierarchical P2P architecture and offers end-to-end consideration of resource provisioning and reliability. We named this system μCloud and characterizes it as a self-provisioning cloud service platform. It is designed, implemented and presented in this dissertation. Eventually, we assessed our work by showing that μCloud succeeds in providing user-centric services using a P2P computing unit. With this, we conclude that our system would be highly beneficial in both small and massively deployed environments.
KMBT_223
Adobe Acrobat 9.51 Paper Capture Plug-in
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Zhang, Bo. "Self-optimization of infrastructure and platform resources in cloud computing." Thesis, Lille 1, 2016. http://www.theses.fr/2016LIL10207/document.

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Анотація:
L’élasticité est pensée comme une solution importante pour gérer des problèmes de performance dans les systèmes répartis. Toutefois, la plupart des recherches d’élasticité ne concernent que l’approvisionnement de ressources de manière automatique, mais ignorent toujours l’utilisation des ressources provisionnées. Cela pourrait conduire à des fuites de ressources, ce qui entraîne des dépenses inutiles. Pour éviter des problèmes, mes recherches se concentrent donc sur la maximisation de l’utilisation des ressources par l’auto-gestion des ressources. Dans cette thèse, en raison de divers problèmes de l’utilisation des ressources dans les différentes couches, je propose deux approches de gestion de ressources correspondant à l’infrastructure et la plate-forme, respectivement. Pour surmonter la limitation des infrastructures, je propose CloudGC comme service de middleware qui vise à libérer les ressources occupées par machines virtuelles qui tournent au ralenti. Dans la couche de plate-forme, une approche d’auto-équilibrage est introduite pour ajuster la configuration de Hadoop lors de l’exécution, ce qui optimise dynamiquement les performances de système. Enfin, cette thèse aussi concerne le déploiement rapide de Hadoop. Un nouvel outil, appelé "hadoop-benchmark", applique docker pour accélérer l’installation de Hadoop et fournir un ensemble d’images de docker qui contiennent plusieurs Hadoop benchmarks bien connus. Les évaluations montrent que ces approches et cet outil peuvent parvenir à l’auto-gestion des ressources dans différentes couches, puis de faciliter l’élasticité de l’infrastructure et de la plate-forme dans le Cloud computing
Elasticity is considered as an important solution to handle the performance issues in scalable distributed system. However, most of the researches of elasticity only concern the provisioning and de-provisioning resources in automatic ways, but always ignore the resource utilization of provisioned resources. This might lead to resource leaks while provisioning redundant resources, thereby causing unnecessary expenditure. To avoid the resource leaks and redundant resources, my research therefore focus on how to maximize resource utilization by self resource management. In this thesis, relevant to diverse problems of resource usage and allocation in different layers, I propose two resource management approaches corresponding to infrastructure and platform, respectively. To overcome infrastructure limitation, I propose CloudGC as middleware service which aims to free occupied resources by recycling idle VMs. In platform-layer, a self-balancing approach is introduced to adjust Hadoop configuration at runtime, thereby avoiding memory loss and dynamically optimizing Hadoop performance. Finally, this thesis concerns rapid deployment of service which is also an issue of elasticity. A new tool, named "hadoop-benchmark", applies docker to accelerate the installation of Hadoop cluster and to provide a set of docker images which contain several well-known Hadoop benchmarks.The assessments show that these approaches and tool can well achieve resource management and self-optimization in various layers, and then facilitate the elasticity of infrastructure and platform in scalable platform, such as Cloud computing
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Gunapati, Venkat Yashwanth. "CLOUD BASED DISTRIBUTED COMPUTING PLATFORM FOR MULTIMODAL ENERGY DATA STREAMS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1399373847.

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Книги з теми "Cloud computing platform"

1

Cloud computing with the Windows Azure Platform. Indianapolis, IN: Wiley Pub., 2009.

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Tony, Guidici, ed. Windows Azure platform. 2nd ed. [Berkeley, Calif.]: Apress, 2011.

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Claudio, Ferracchiati Fabio, ed. Windows Azure platform. [Berkeley, Calif.]: Apress, 2009.

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Hurwitz, Judith. Platform as a service for dummies. Hoboken, NJ: John Wiley & Sons, 2012.

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Wood, James. Getting started with SAP HANA cloud platform. Bonn: Rheinwerk Publishing, 2015.

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Glen, Martin, Fawcett Andrew, and Choi Phil, eds. The developer's guide to the Force.com platform. [United States?]: Salesforce.com, 2008.

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Force platform fundamentals: An introduction to custom application development in the cloud. [United States?]: Salesforce.com, 2008.

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Microsoft Azure yun duan cheng shi she ji: Shi yong ASP.NET MVC kai fa. Xinbei Shi: Bo shuo wen hua gu fen you xian gong si, 2016.

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Moving applications to the cloud on the Microsoft Windows Azure platform. [Redmond, Wash.]: Microsoft, 2010.

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Betts, Dominic. Moving applications to the cloud on the Microsoft Windows Azure platform. [Redmond, Wash.]: Microsoft, 2010.

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Частини книг з теми "Cloud computing platform"

1

Ji, Shujian, Kejiang Ye, and Cheng-Zhong Xu. "CMonitor: A Monitoring and Alarming Platform for Container-Based Clouds." In Cloud Computing – CLOUD 2019, 324–39. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_23.

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Hassan, Mohammad Mehedi, and Eui-Nam Huh. "Overview of Cloud Computing and Motivation of the Work." In Dynamic Cloud Collaboration Platform, 1–12. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5146-4_1.

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3

González, Roberto, Daniel Hernández, Fernando De la Prieta, and Ana Belén Gil. "+Cloud: An Agent-Based Cloud Computing Platform." In Distributed Computing and Artificial Intelligence, 377–84. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00551-5_46.

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Machiraju, Suren, and Suraj Gaurav. "Introducing the Cloud Computing Platform." In Hardening Azure Applications, 1–22. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-0920-2_1.

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Slawinska, Magdalena, Jaroslaw Slawinski, and Vaidy Sunderam. "Towards Cross-Platform Cloud Computing." In Euro-Par 2011: Parallel Processing Workshops, 5–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29737-3_2.

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Machiraju, Suren, and Suraj Gaurav. "Introducing the Cloud Computing Platform." In Hardening Azure Applications, 1–41. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-4188-2_1.

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Zhang, Yonghe, Kejiang Ye, and Cheng-Zhong Xu. "An Experimental Analysis of Function Performance with Resource Allocation on Serverless Platform." In Cloud Computing – CLOUD 2021, 17–31. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96326-2_2.

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Eggert, Michael, Daniel Kerpen, Kirsten Rüssmann, and Roger Häußling. "SensorCloud: Sociological Contextualization of an Innovative Cloud Platform." In Trusted Cloud Computing, 295–313. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12718-7_18.

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Zhuo, Yue. "Application of Computing Platform in Cloud Computing." In Lecture Notes in Electrical Engineering, 2339–43. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0115-6_289.

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Amini Salehi, Mohsen, and Xiangbo Li. "Prototype Implementation of the MSC Platform." In Multimedia Cloud Computing Systems, 163–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88451-2_9.

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Тези доповідей конференцій з теми "Cloud computing platform"

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Lee, Jaehun, Hochul Lee, Young Choon Lee, Hyuck Han, and Sooyong Kang. "Platform Support for Mobile Edge Computing." In 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). IEEE, 2017. http://dx.doi.org/10.1109/cloud.2017.84.

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Loganayagi, B., and S. Sujatha. "Cloud computing in Stax Platform." In 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET). IEEE, 2011. http://dx.doi.org/10.1109/icccet.2011.5762436.

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Sefraoui, Omar, Mohammed Aissaoui, and Mohsine Eleuldj. "Management platform for Cloud Computing." In 2015 International Conference on Cloud Technologies and Applications (CloudTech). IEEE, 2015. http://dx.doi.org/10.1109/cloudtech.2015.7336968.

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Vieira, Lucas, Adbys Vasconcelos, Ítalo Batista, Rodolfo A. M. Silva, and Francisco Brasileiro. "DisOpenFaaS: A Distributed Function-as-a-Service Platform." In XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbrc_estendido.2019.7767.

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Анотація:
The adoption of cloud computing is increasing due to low costs of infrastructure, as well as having virtually infinite resources available for demand based scaling. The increasing interest in this topic, there is a continuous search for better ways to manage such infrastructures. One of the most recent steps was the development of Function-as-a-Service (FaaS). FaaS is a cloud computing service model where developers can deploy functions to a cloud platform and have them executed based on the triggering of events, or by making HTTP(S) requests. We propose an architecture for deploying FaaS platforms in hybrid clouds that can be composed by multiple cloud providers. This architecture enable privately deployed FaaS platforms to perform auto-scaling of virtual machines in a distributed infrastructure, while considering the scenario where the users of such platform are scattered around the globe. This allows the execution of requests in servers geographically located as close as possible from the client.
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Shen, Zhidong, Li Li, Fei Yan, and Xiaoping Wu. "Cloud Computing System Based on Trusted Computing Platform." In 2010 International Conference on Intelligent Computation Technology and Automation (ICICTA). IEEE, 2010. http://dx.doi.org/10.1109/icicta.2010.724.

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Roloff, Eduardo, Francis Birck, Matthias Diener, Alexandre Carissimi, and Philippe O. A. Navaux. "Evaluating High Performance Computing on the Windows Azure Platform." In 2012 IEEE 5th International Conference on Cloud Computing (CLOUD). IEEE, 2012. http://dx.doi.org/10.1109/cloud.2012.47.

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Falfushinsky, Vladislav, Olena Skarlat, and Vadim Tulchinsky. "Cloud computing platform within Grid Infrastructure." In 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). IEEE, 2013. http://dx.doi.org/10.1109/idaacs.2013.6663018.

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8

Loganayagi, B., and S. Sujatha. "Creating virtual platform for cloud computing." In 2010 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). IEEE, 2010. http://dx.doi.org/10.1109/iccic.2010.5705744.

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Xiaoping, Xu, and Yan Junhu. "Research on Cloud Computing Security Platform." In 2012 Fourth International Conference on Computational and Information Sciences (ICCIS). IEEE, 2012. http://dx.doi.org/10.1109/iccis.2012.238.

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Jarraya, Y., A. Eghtesadi, M. Debbabi, Y. Zhang, and M. Pourzandi. "Cloud calculus: Security verification in elastic cloud computing platform." In 2012 International Conference on Collaboration Technologies and Systems (CTS). IEEE, 2012. http://dx.doi.org/10.1109/cts.2012.6261089.

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Звіти організацій з теми "Cloud computing platform"

1

Birman, Ken. Platform for High-Assurance Cloud Computing. Fort Belvoir, VA: Defense Technical Information Center, June 2016. http://dx.doi.org/10.21236/ad1010441.

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Bartock, Michael, Murugiah Souppaya, Ryan Savino, Tim Knoll, Uttam Shetty, Mourad Cherfaoui, Raghu Yeluri, et al. Hardware-Enabled Security: Enabling a Layered Approach to Platform Security for Cloud and Edge Computing Use Cases. National Institute of Standards and Technology, October 2021. http://dx.doi.org/10.6028/nist.ir.8320-draft2.

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Oleksiuk, Vasyl P., Olesia R. Oleksiuk, Oleg M. Spirin, Nadiia R. Balyk, and Yaroslav P. Vasylenko. Some experience in maintenance of an academic cloud. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4436.

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The article is devoted to the systematization of experience in the deployment, maintenance and servicing of the private academic cloud. The article contains model of the authors’ cloud infrastructure. It was developed at Ternopil Volodymyr Hnatiuk National Pedagogical University (Ukraine) on the basis of the Apache CloudStack platform. The authors identify the main tasks for maintaining a private academic cloud. Here they are making changes to the cloud infrastructure; maintenance of virtual machines (VM) to determine the performance and migration of VM instances; work with VMs; backup of all cloud infrastructure. The analysis of productivity and providing students with computing resources is carried out. The main types of VM used in training are given. The number and characteristics of VM that can be served by a private academic cloud are calculated. Approaches and schemes for performing backup are analysed. Some theoretical and practical experience of using cloud services to perform backup has been studied. Several scripts have been developed for archiving the platform database and its repositories. They allow you to upload backups to the Google Drive cloud service. The performance of these scripts for the author’s deployment of private cloud infrastructure was evaluated.
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Zhylenko, Tetyana I. Auto Checker of Higher Mathematics - an element of mobile cloud education. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3895.

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We analyzed the main cloud services in the article. We also described the main contribution of mobile cloud technology to education. The article presents the author’s development from the field of mobile cloud education in higher mathematics. The design architecture of this application is described in detail: QR generator and scanner, authorization, sending tasks. Block diagrams and images are presented that clearly demonstrate the operation of the application. We showed an example of solving the integral from the section of integral calculus for higher mathematics and showed how to download the answer in the form of a QR code and find out whether it is correct or incorrect (this can be seen by the color on the smart phone screen). It is shown how this technology helps the teacher save time for checking assignments completed by students. This confirms its effectiveness. Such an application provides students and teachers with the ability to store and process data on a cloud computing platform.
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Solovyanenko, Nina I. ЮРИДИЧЕСКИЕ СТРАТЕГИИ ЦИФРОВОЙ ТРАНСФОРМАЦИИ АГРАРНОГО БИЗНЕСА. DOI CODE, 2021. http://dx.doi.org/10.18411/0131-5226-2021-70004.

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Анотація:
t.The development of global agricultural production and food trade in recent decades implies a digital transformation and the transition to a new technological order, which is an essential factor for sustainable development. Digitalization of agriculture and the food sector is carried out on the basis of IT 2 platforms, the Internet of Things, cloud computing, big data, artificial intelligence, and blockchain technology. Fragmented and unclear legal mechanisms, slow updating of legal regulation hinder the introduction of digital solutions. A modern regulatory framework based on digital strategies should strengthen the confidence of farmers in "smart agriculture". In Russia, the legal mechanism of strategic planning covers the development of the national platform "Digital Agriculture". Digital strategies also include updating basic legislation.
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Solovyanenko, Nina I. Legal features of innovative (digital) entrepreneurship in the agricultural and food sector. DOI CODE, 2021. http://dx.doi.org/10.18411/0131-5226-2021-70008.

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Анотація:
Modern agricultural production and food trade are involved in the process of digital transformation, which is a cardinal factor of sustainable development and is carried out on the basis of IT platforms, the Internet of Things, cloud computing, big data, artificial intelligence, blockchain technologies. The COVID-19 pandemic has increased the dependence of these sectors of the economy on information and communication technology infrastructure and services. At the same time, the slow updating of legislation, which lags behind the constantly improving digital technologies, not only hinders their implementation, but also is a source of a number of social and legal problems. A modern regulatory framework based on digital strategies should strengthen "smart agriculture". In Russia, the legal mechanism of digital transformation and development of the national platform "Digital Agriculture" should be supported by updated basic legislation.
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Varina, Hanna B., Viacheslav V. Osadchyi, Kateryna P. Osadcha, Svetlana V. Shevchenko, and Svitlana H. Lytvynova. Peculiarities of cloud computing use in the process of the first-year students' adaptive potential development. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4453.

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Анотація:
Technologies based on cloud computing is one of the demanded and actively developing areas of the modern information world. Cloud computing refers to an innovative technology that allows you to combine IT resources of various hardware platforms into a single whole and provide the user with access to them via a local network or the global Internet. Cloud services from various providers offer users access to their resources via the Internet via free or shareware cloud applications, the hardware and software requirements of which do not imply that the user has high-performance and resource-consuming computers. Cloud technologies represent a new way of organizing the educational process and offers an alternative to traditional methods of organizing the educational process, creates an opportunity for personal learning, collective teaching, interactive classes, and the organization of psychological support. The scientific article is devoted to the problem of integrating cloud technologies not only in the process of training highly qualified specialists, but also in the formation of professionally important personality traits. The article describes the experience of introducing cloud technologies into the process of forming the adaptive potential of students in conditions of social constraints caused by the COVID-19 pandemic.
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Oleksiuk, Vasyl P., and Olesia R. Oleksiuk. Methodology of teaching cloud technologies to future computer science teachers. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3891.

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The article deals with the problem of training future computer science teachers for the use of cloud technologies. The authors analyzed courses from leading universities to study cloud technologies. On this basis the model of application and studying of cloud technologies in the process of training of future teachers of informatics was developed. The basic principles of this model are proposed: systematic, gradual, continuous. It contains target, content, operating and effective component. Therefore, the stages of using cloud computing technology were proposed: as a means of organizing learning activities, as an object of study, as a means of development. The article summarizes the experience of designing a cloud-based learning environment (CBLE). The model is based on such philosophical and pedagogical approaches as systemic, competent, activity, personality-oriented, synergistic. Hybrid cloud is the most appropriate model for this environment. It combines public and private cloud platforms. CBLE also requires the integration of cloud and traditional learning tools. The authors described the most appropriate teaching methods for cloud technologies such as classroom learning, interactive and e-learning, practical methods. The article contains many examples of how to apply the proposed methodology in a real learning process.
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Iatsyshyn, Anna V., Valeriia O. Kovach, Yevhen O. Romanenko, and Andrii V. Iatsyshyn. Cloud services application ways for preparation of future PhD. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3248.

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Анотація:
Currently, it is important in Ukraine to harmonize cloud technologies application with European and world scientific initiatives. Need to modernize preparation of future PhDs is caused by challenges of new information, globalized society and digital transformation of all spheres of life, including education and science. The research was aimed to determine features of cloud services application in preparation of future PhDs. Concepts of “cloud computing”, “cloud technologies”, “cloud learning technologies”, “cloud services”, “cloud oriented environment” were analyzed. Experience of cloud technologies and their services application in educational and scientific space in researches of foreign and Ukrainian students was considered. Ukrainian experience in preparation of future PhD of various specialties with cloud services application was analyzed. It was emphasized that approaches improving to preparation of future PhDs based on cloud services application would increase their level of digital competence. It is recommended to include a separate course or module of specific discipline on work with cloud technologies and services during preparation of future PhDs. It is important to improve disciplines and tools content to support education process. It can be learning of disciplines using cloud technologies or services by future PhD’s. Also, cloud services application to support scientific and scientific-organizational activities will increase level of organization and implementation of scientific research. It is important to create cloud-oriented environment for preparation of future PhDs in higher education and research institutions. Making cloud-oriented educational and scientific environment should be based on principles of open education. It is recommended to use cloud-based platforms and services (G Suite for Education; Microsoft Office 365; specialized SaaS (CoCalc or other)).
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Kaleagasi, Bartu, Sean McCarthy, and Peter Beaumont. Geospatial Public Policy: Global Best Practices for Harnessing the Potential of Satellite Technologies and Applications. Inter-American Development Bank, September 2022. http://dx.doi.org/10.18235/0004484.

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Анотація:
This publication presents six case studies of public policies that promote the development and use of geospatial technologies and applications, which can be categorized in five layers: institutions, tools, data, skills and industry. The evolution of these technologies and applications over the past decade has been driven by the understanding that where people and things are located is central to smart decision making. As a result of low-cost launch vehicles, increasing numbers of satellites in orbit, new sensor technologies, machine learning algorithms, advances in cloud computing, and the emergence of other technologies such as drones and high-altitude platforms, the geospatial economy is now expanding into many new geographies and sectors. This expansion calls for the development of innovative applications that benefit government in areas such as agriculture, environment, energy, aviation, maritime, transport, health, education, business, and society.
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