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Dissertations / Theses on the topic 'Google Cloud Services'
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1
Quadri, S. (Samsideen). "Cloud computing:migrating to the cloud, Amazon Web Services and Google Cloud Platform." Master's thesis, University of Oulu, 2017. http://urn.fi/URN:NBN:fi:oulu-201703151365.
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Cloud computing provides great benefits and challenges for small, medium, and large organisations. Whether it is a financial, technology, or engineering sector any company may find a useful cloud component for the organisation’s needs. Though with its benefits come many challenges, experts believe that cloud computing advantages outweigh the disadvantages. With more research in the area of cloud computing, the challenges will be dealt with.
Amazon and Google are the prominent cloud services providers with different components and services that are evolving. However, there are many other cloud vendors and this makes it difficult for potential cloud users to migrate or choose a suitable vendor from the numerous available ones.
This thesis, using design science approach describes the implementation of cloud computing by different cloud providers, i.e., examines and demonstrates how Amazon and Google implemented and structured their cloud infrastructure. Also, it provides the criteria for accessing the suitability of a business or organisation for choosing a cloud provider. In addition, a web application hosted on both AWS and GCP platforms is developed in order to demonstrate the workability of the framework and guideline for selecting a cloud provider. The application is called KlaudCelet. KlaudCelet is a recommender system that is developed based on previous research on cloud deployment frameworks and proposed model (CPSM; Cloud Provider Selection Model). The recommendation by the system is reliable because it is based on research results. KlaudCelet recommends a deployment model, a cloud service provider, and a decision either to migrate or not. CPSM was not used in KlaudCelet but the model by Keung & Kwok and Misra & Mondal were used.
The guideline developed was used to create a recommender framework. The need for solving this problem was shown by conducting a review of previous research and a small-scale survey among IT experts. The survey found that IT experts are optimistic about cloud computing adoption despite its challenges such as security, privacy and leaning curve. The decision to migrate to the cloud must take into consideration the organisation’s state and culture, cloud deployment model, and choosing a suitable cloud service provider.
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Bandini, Alessandro. "Programming and Deployment of Cloud-based Data Analysis Applications." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13803/.
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Cloud Computing constitutes a model capable of enabling the network access in a shared, practical and on demand of different computational resources like networks, memory, application or services.
This work has as goal the explanation of the project made within Cloud Computing. After an introduction of the theory that lies behind Cloud computing's technologies, there is the practical part of the the work, starting from a more specific platform, Hadoop, which allows storage and data analysis and then moving to more general purpose platforms, Amazon Web Services and Google App Engine, where different types of services have been tried. The major part of the project is based on Google App Engine, where storage and computational services have been used to run MapReduce jobs. MapReduce is a different programming approach for solving data analysis problems, that is suited for big data. The first jobs are written in python, an imperative programming language. Later on, a functional approach on the same problems has been tried, with the Scala language and Spark platform, to compare the code.
As Cloud computing is mainly used to host websites, a simple site was developed as integral part of the work. The development of the site is not explained as it goes beyond this thesis' main focus, only the relevant aspects will be treated.
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Englund, Carl. "Evaluation of cloud-based infrastructures for scalable applications." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139935.
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The usage of cloud computing in order to move away from local servers and infrastructure have grown enormously the last decade. The ability to quickly scale capacity of servers and their resources at once when needed is something that can both be a price saver for companies and help them deliver high end products that will function correctly at all times even under heavy load to their customers. To meet todays challenges, one of the strategic directions of Attentec, a software company located in Linköping, is to examine the world of cloud computing in order to deliver robust and scalable applications to their customers. This thesis investigates the usage of cloud services in order to deploy scalable applications which can adapt to usage peaks within minutes.
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Talevi, Iacopo. "Big Data Analytics and Application Deployment on Cloud Infrastructure." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14408/.
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This dissertation describes a project began in October 2016. It was born from the collaboration between Mr.Alessandro Bandini and me, and has been developed under the supervision of professor Gianluigi Zavattaro. The main objective was to study, and in particular to experiment with, the cloud computing in general and its potentiality in the data elaboration field.
Cloud computing is a utility-oriented and Internet-centric way of delivering IT services on demand.
The first chapter is a theoretical introduction on cloud computing, analyzing the main aspects, the keywords, and the technologies behind clouds, as well as the reasons for the success of this technology and its problems. After the introduction section, I will briefly describe the three main cloud platforms in the market.
During this project we developed a simple Social Network. Consequently in the third chapter I will analyze the social network development, with the initial solution realized through Amazon Web Services and the steps we took to obtain the final version using Google Cloud Platform with its charateristics.
To conclude, the last section is specific for the data elaboration and contains a initial theoretical part that describes MapReduce and Hadoop followed by a description of our analysis. We used Google App Engine to execute these elaborations on a large dataset. I will explain the basic idea, the code and the problems encountered.
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Величко, Георгій Вячеславович. "Методи та засоби прогнозування індексу акцій у реальному часі на базі хмарних обчислювальних сервісів." Master's thesis, КПІ ім. Ігоря Сікорського, 2021. https://ela.kpi.ua/handle/123456789/46687.
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Магістерська дисертація: 92 с., 28 рис., 21 табл., 1 дод., 30 джерел.
Тема роботи — Методи та засоби прогнозування індексу акцій у
реальному часі на базі хмарних обчислювальних сервісів.
Об’єкт дослідження — методи прогнозування акцій на базі хмарних
обчислювальних сервісів.
Предмет досліджень — багатошарова нейронна мережа, згорткова
нейронна мережа та мережа довгої короткочасної пам’яті, хмарні обчислювальні
сервіси, Amazon Web Services.
Мета роботи — підвищити ефективність прогнозування індексу акцій на
базі хмарних обчислювальних сервісів та розробити модель реалізації системи
на базі хмарних сервісів.
Актуальність — використання апарату штучних нейронних мереж дає
змогу робити більш точні передбачення ціни акцій порівнюючи з іншими
технічними методами. Хмарні сервіси забезпечують швидке та гнучке
розгортання інфраструктури, забезпечує їх повсякчасну доступність.
В ході виконання роботи було реалізовано декілька ахітектур нейронних
мереж та проведено аналіз результатів їх роботи. Також було cпроектовано
систему прогнозування індексу акцій в реальному часі на базі хмарних сервісів.
Для покращення результатів у майбутньому можна застосувати Keras
Tuner, який автоматично підбирає гіперпараметри нейронної мережі. Також
можна використовувати додаткову інформацію про компанію і додавати ці дані
до моделей.Master`s thesis contains: 92 p., 21 tables, 28 fig., 1 add. and 30 references. The theme: The mechanisms tools for real-time stock market index prediction based on Cloud Compute Services. The objects of this research are mechanisms for stock market index prediction based on Cloud Compute Services. The subjects of this research are neural network architectures: multilayer neural network, convolutional neural network, long short-term memory, cloud compute services, Amazon Web Services. The purpose of this work is to improve efficiency of stock market index prediction based on Cloud Compute Services and design model of system for stock market index forecasting based on Cloud Compute Services. The relevance of this topic is that using neural networks could drastically improve stock market values forecasting comparing to other technical methods. Cloud compute services provides fast and flexible deployment of infrastructure as well as constant availability. Also designed a model of system for real-time stock index forecasting based on cloud compute services. During research I built three architectures of neural networks and analyzed which of them work better with the given case. For further research, it is possible to use Keras Tuner which allows to automatically tune hyperparameters on our neural network and improve output result. Also, additional data about companies provided real-time can improve models.
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Göthesson, Richard, and Gustav Hedman. "Autentiseringsprocesser i molnbaserade datortjänster." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20452.
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Tidigare forskning har påvisat brister i olika former av autentiseringsprocesser som leder till autentiseringsattacker. Målet med vår studie är att presentera ett antal riktlinjer som företag och privatpersoner kan följa för att minimera risken för autentiseringsattacker. Metoderna som användes för att komma fram till dessa riktlinjer var kvalitativa där en praktisk observationsstudie, en litteraturstudie samt en enkätundersökning låg till grund för vår insamlade data. Resultatet av studien pekar på att Google Cloud Platform, Amazon Web Services och Microsoft Azure alla har en stark autentiseringsprocess i jämförelse med kritik från tidigare forskning. Enkätundersökningen visade dessutom att olika former av alternativ autentisering, såsom Two Factor Authentication (2FA) och Multi Factor Authentication (MFA), rekommenderas för ett starkt försvar mot autentiseringsattacker.Uppsatsens resultat pekar även på att användarens egenansvar i autentiseringsprocessen är av stor vikt för att minimera risken för autentiseringsattacker. Säkra lösenord bör konstrueras och frekvent bytas ut. Även alternativ autentisering och begränsning av användarens tillgång till känslig information bör tillämpas.Previous research has shown deficiencies in various forms of authentication processes that lead to authentication attacks. The goal of our study is to present a number of guidelines that businesses and individuals can follow to minimize the risk of authentication attacks. The methods used to reach these guidelines were qualitative. They consisted of a practical observational study, a literature review and a survey, which formed the basis of our collected data. The results of the study indicate that Google Cloud Platform, Amazon Web Services and Microsoft Azure all have a strong authentication process in comparison with the criticism of previous research. The survey also showed that different forms of authentication methods, such as the Two Factor Authentication (2FA) and Multi Factor Authentication (MFA), are recommended for a strong defense against authentication attacks.The thesis’ results also points to the user’s own responsibility in the authentication process are essential to minimize the risk of authentication attacks. Secure passwords should be designed and frequently replaced. Alternative authentication and restricted access to sensitive information for the user should also be applied.
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Torelli, Mattia. "Notifiche push in applicativi Android: uso di gcm ed una soluzione alternativa basata su long-polling http." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7574/.
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Vengono presentate due soluzioni per le notifiche push in ambiente Android: le soluzioni trattate riguardano l'uso di GCM (Google Cloud Messaging) ed una implementazione che impiega il Long-Polling HTTP come alternativa al servizio GCM.
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Cavallin, Riccardo. "Approccio blockchain per la gestione dei dati personali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21604/.
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L'elaborato presenta la tecnologia blockchain nelle sue funzionalità e nei suoi limiti. In particolare sono presentate le piattaforme Ethereum, RadixDLT e IOTA. Vengono discusse le implicazioni del regolamento GDPR nei confronti di questa tecnologia per la costruzione di Data Marketplace basato su Ethereum. Dopo aver presentato l'architettura di un marketplace si analizzano le prestazioni di diversi servizi di storage online per l'archiviazione di dati personali.
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Galavotti, Serena. "Contacts Sharing: integrazione tra CRM e il cloud Google." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6747/.
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Kutil, Ivan. "Google jako enterprise řešení firmy." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-85156.
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The diploma thesis deals with the topic of cloud computing and its appropriate deployment in small and medium business. The objective of this thesis is to analyze the offer of Google products and to demonstrate measurable benefits of this solution. Introductory part of the thesis summarizes the history of IT and it is looking for the connection between history of IT and the term cloud computing. This term is described in detail with selected cloud computing characteristics. The main part of the thesis deals with analysis of Google services, technologies and platforms, which could be used in enterprise. The matters are viewed not only economically, but also from the technological and security point of view. In practical implementations are demonstrated measurable benefits of deployment to the Google cloud platform. Finally, the thesis provides the summary of platform's advantages and disadvantages with a description of practical advices for small and medium businesses
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Ersson, Sara, and Oskar Dahl. "Specialization of an Existing Image Recognition Service Using a Neural Network." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-232072.
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To help combat the environmental impacts caused by humans this project is about investigating one way to simplify the waste management process. The idea is to use image recognition to identify what material the recyclable object is made of. A large data set containing labeled images of trash, called Trashnet, was analyzed using Google Cloud Vision. Since this API is not written for material detection specifically, a feed forward neural network was created using Tensorflow and trained with the output from Google Cloud Vision. Thus, the network learned how different word combinations from Google Cloud Vision implicated one of five different materials; glass, plastic, paper, metal and combustible waste. The network checked for 518 unique words in the input and ran them through two hidden layers with a size of 1000 nodes each, before having a one hot output layer. This neural network received an accuracy of around 60%, which beat Google Cloud Vision’s meager accuracy of around 30%. An application, with which the user can take pictures of the object he or she would like to recycle, could be developed with an educational purpose to let its user know what material the waste is made of, and with this information be able to throw the waste in the right bin.För att hjälpa till att motverka människans negativa påverkan på miljön kommer detta projekt handla om att undersöka hur man kan göra det enklare att källsortera. Grundidén är att använda bildigenkänning för att identifiera vilket återvinningsbart material som objektet i bilden består av. Ett stort dataset med bilder indelade i olika återvinningsbara material, kallat Trashnet, analyserades med hjälp av Google Cloud Vision, vilket är ett API för bildigenkänning och inte specifikt igenkänning av material. Med hjälp av Tensorflow skapades ett neuralt nätverk som använder utdatan från Google Cloud Vision som indata, vilket i sin tur kan ge ett av fem olika material som utdata; glas, plast, papper, metall eller brännbart. Nätverket lärde sig hur olika ordkombinationer från Google Cloud Vision implikerade ett av de fem materialen. Nätverkets indata-lager består av de 518 unika orden som Google Cloud Vision sammanlagt gav som utdata efter att ha analyserade Trashnets dataset. Dessa ord körs igenom två dolda lager, vilka båda består av 1000 noder var, innan det sista lagret, som är ett ”one hot”-utdatalager. Detta nätverk fick en träffsäkerhet på cirka 60%, vilket slog Google Cloud Visions träffsäkerhet på cirka 30%. Detta skulle kunna användas i en applikation, där användaren tar en bild på det skräp som önskas återvinnas, som utvecklas i utbildningssyfte att lära användaren vilket material dennes återvinningsbara föremål är gjort av, och med denna information bättre kunna källsortera.
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Faisal, Chaudhry Muhammad Nadeem. "Usability Evaluation of Cloud Based Application." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5566.
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The students mostly use web based services for achieving their goals in education. They need these services for different purposes. The usability aspect is a need to design these services to be more interactive in order to support the students at their work. Google Docs is the link to the concept Software as a service i.e. a type of cloud computing. A web based application that provides online resource to the users for creating, editing and storing their documents online. The author particularly discusses it from the Student’s perspective. Usability evaluation of the Google Docs is to find the students needs and requirements and also to investigate the usability issues in Google Docs. In this thesis the author is trying to uncover the usability and privacy related problems faced by the students. This is helpful in analyzing the Google Docs (Software as a service) and its importance, by considering the students perspective. Different usability methods and techniques are available for usability evaluation. The author adopted Think Aloud (TA), questionnaires and interview to evaluate the usability of Google Docs.
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Прасол, Ю. П. "Веб-застосування салону краси." Thesis, Чернігів, 2021. http://ir.stu.cn.ua/123456789/24976.
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Прасол, Ю. К. Веб-застосування салону краси : випускна кваліфікаційна робота : 123 "Комп’ютерна інженерія" / Ю. К. Прасол ; керівник роботи О. А. Пріла ; НУ "Чернігівська політехніка", кафедра інформаційних і комп’ютерних систем. – Чернігів, 2021. – 88 с.Метою кваліфікаційної роботи магістра – створення клієнт-серверного застосування для салону краси. Результатом роботи є реалізація таких можливостей: - Реєстрація та авторизація клієнтів на сервері - Можливість оформлення запису на послугу - Можливість здійснення покупок в магазині На стороні серверу працює Node.js платформа. Реалізація застосунку була виконана з використанням технологій JavaScript, Node.js, React-bootstrap, PostgreSQL. Для реалізації системи використовувались інструментальні засоби VSCode 1.62.3 Подальша розробка застосунку можлива в сторону розширення функціоналу та підвищення швидкості. Робота має практичну цінність. Розрахунок економічної цінності не проводився.
The object of study is a client-server application. The purpose of the master's qualification work is to create a client-server application for a beauty salon. The result is the realization of the following opportunities: - Registration and authorization of clients on the server - Ability to register for the service - Ability to shop in the store The Node.js platform runs on the server side. The implementation of the application was performed using JavaScript, Node.js, React-bootstrap, PostgreSQL. VSCode 1.62.3 tools were used to implement the system Further development of the application is possible in the direction of expanding functionality and increasing speed. The work has practical value. The calculation of economic value was not performed.
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Bobák, Petr. "Mobilní systém pro rozpoznání textu na iOS." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363789.
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This thesis describes a development of a modern client-server application for text recognition on iOS platform. The reader is acquainted with common principles of a client-server model, including its known architecture styles, and with a distribution of logical layers between both sides of the model. After that the thesis depicts current trends and examples of suitable technologies for creating an application programming interface of a web server. Possible ways of text recognition on the server side are discussed as well. In context of a client side, the thesis provides an insight into iOS platform and a few important concepts in iOS application development. Following implementation of the server side is stressed to be reusable as much as possible for different kinds of use cases. Last but not least, the thesis provides a simple iOS framework for a direct communication with the recognition server. Finally, an application for evaluation of food ingredients from a packaging material is implemented as an example of usage.
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Liao, Zi-yi, and 廖子毅. "The Exploration of Building E- Service Model Based on Google Cloud Services." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/31947904891482111015.
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碩士國立屏東教育大學
資訊科學系
100
With the high rapid development on technology information in recent years, a number of the major technological progresses are to guide the emergence of Internet. Because of the highly novelty and change in the market mechanism, it set off another wave of the enterprise revolution once again. One of the most critical part is that Internet has become the service platform which can concatenate multiple virtual shopping carts as well as support different types of platforms. Under the generation of Internet, it has fueled the e-commerce development which establishing trading patterns to reduce the significantly cost, to enhance the trading efficiency, etc. That is why many multinational companies are so optimistic about the e-commerce market. So far, the Internet has made a lot of successful e-commerce business models such as Amazon and Apple. Therefore, how to make benefits of the use of Internet will be the focus of new business model in the future. This research is specializing in building the business website under the Google collaboration platform. By the integration of Google services, it could provide the consistency of the website as well as the low cost of building in order to construct an e-commerce websites with the features of fast, convenient, safe and easy to use.
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CHEN, KUAN-CHOU, and 陳冠洲. "A Study of Continuance Intention to Cloud Application Services-Using Google Cloud Application Software as an Example." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/4m9j5v.
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碩士開南大學
資訊學院碩士在職專班
105
With the development of communication and cloud platform technology, cloud computing is capable of using the Internet as a medium to provide a large number of computing resources to companies and individual users. With legal authorized accounts, users can connect to a cloud-computing platform through the Internet and use the variety of services provided on that platform. The Software-as-a-service (SaaS) is a software delivery model, which uses the cloud computing platform to provide users with various cloud services. Moreover, the prevalence of mobile devices has gradually changed the way people use network facilities, and the use of smart phones and tablet computers for Internet connection to cloud application software has gradually become a trend. By using mobile Internet on their mobile devices, users can access cloud application software for their business, work, collaborative tasks, online meetings, recreational and entertainment needs, and other matters. The convenience, functionality and sharing features of cloud application services indicate great business opportunities and future prospects. However, key factors influencing willingness to use cloud application services are worth exploring. In addition to the basic framework of IS Continuance Model, this study also examined the impact of external factors such as perceived security, system quality, degree of innovation acceptance, motive of using and perceived usefulness on user satisfaction and intention of continuous usage of cloud application services. An empirical questionnaire survey was administered to users of cloud application services through social networking websites. A total of 313 valid questionnaires was collected and analyzed using structural equation modeling software (PLS). The results of this study showed that: (1) Degree of confirmation, perceived security, innovation acceptance, motive of using and perceived usefulness had a positive influence on user satisfaction; and (2) User satisfaction had a positive influence on intention of continuous usage. Practical recommendations based on the analysis results were provided for cloud application service providers for their operation and management, and as reference for follow-up studies. Keywords：Cloud application services、Perceived security、Innovation acceptance、Continuous usage intention.
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Lai, Yi-Ning, and 賴以寧. "Exploring User Stickiness of GOOGLE Cloud Services based on Process Virtualization Theory and Switching Costs." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/83378997454314302934.
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碩士淡江大學
資訊管理學系碩士班
101
With cloud computing technology developed, the users need only connect to the Internet to directly select the services they want to use. Because the service providers provide the basic requirements of the services required by all users, these services are called cloud services. Through the concept of on-demand self-service, users can serve themselves and take advantage of on-demand and immediate use at any time. Most of the past studies of cloud services, however, focused on the technical aspects, rarely touching the service issues. In addition, as virtualization is the most important characteristic of cloud services, this study used the process virtualization theory and combined the switching costs perspective and the uses and gratifications theory to understand the factors influencing the stickiness after the user behavior of cloud services was formed. Data collected from 433 users of Google Cloud Service provide strong support for the research model. The results show: (1)Process virtualization capability is significantly associated with sociability gratification; (2)Process virtualization capability is significantly associated with gratification opportunities; (3)Sociability gratification is significantly associated with stickiness; (4) Gratification opportunities is associated with stickiness; and (5) Switching costs negatively moderated the influence of sociability gratification on stickiness. The study results serve as a reference for cloud service operators in their development of management strategies to enhance cloud service core values.
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Wang, Chia-Chun, and 王家駿. "Distributed Cloud Services Architecture for the Internet of Things System Prototype Based on the Google V8 Engine." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/7ea7ru.
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碩士國立高雄第一科技大學
電腦與通訊工程研究所
105
Although the Internet of Things have been discussed for a long time, most products or design prototypes are often lack of integration. So in this study, we will propose a prototype of a lightweight solution. This solution is using a flexible cloud server as medium to communicate between objects and their applications. The proposed lightweight solution can apply to local-side server. All devices use this server to connect to the network, and that network can store logs, push instantly messages and handle controls instantly. And the complexity of this proposed solution is low. A new real-time web interface is introduced.
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Lu, Yun-Tung, and 呂蘊桐. "Examining Critical Factors Influencing SME Adoption Intention of Cloud SaaS Services - Take Google Apps for Business for Instance." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/gpr95t.
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碩士國立中正大學
資訊管理學系暨研究所
103
The cloud computing has no doubt been the biggest innovation in the information technology industry in the 21th century. All major international information technology companies have aggressively invested in the cloud computing technology. New hardware, networks, platforms and software were developed based on the three service models introduced by NIST (National Institute of Standards and Technology, U.S. Department of Commerce): the Infrastructure as a Service (IaaS), the Platform as a Service (PaaS), and the Software as a Service (Saas). Investing in information and computing infrastructure has always been the lowest priority for Taiwan’s SMEs. This has been the case due to limited budgets and resources. Recently this situation has a dramatic change thanks to the rise of the cloud computing industry. The Saas services from cloud computing has injected new life into the SMEs, created huge business opportunities. This study has referenced Technology, Organization and Environment Framework (TOE). Together with relevant research literatures and distinct characteristics SaaS services from the cloud computing, this study produced a new research model. This research model focused on the impact to the SMEs after adopting the Saas services from the cloud computing. This model studied key factors that impacted SMEs from four contexts, the technology context, the organization context, the environmental context, and the SaaS provider context. In this study, 213 valid questionnaires were collected, analyzed questionnaire data by using discriminant analysis method, The results show the following factors can help SMEs to adopt cloud services intention effects are significant, those factors are :"Information Security", "Use to anytime, anywhere", "Firm size", "Regulatory support", "Competitive pressure", "Service Level Agreements" and "Trial Service". The results of this study can be used as industry, government and academia and cloud SaaS service providers to assist SMEs to adopt SaaS cloud services as a planning reference.
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Wu, Jianyi, and 吳建億. "Using Google Cloud Services to Study Web-based Collaborative Learning-A Case Study of Social Studies in Elementary School." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/54937143599831922889.
Full textAbstract:
碩士靜宜大學
資訊碩士在職專班
101
With the new era of Web 2.0 and cloud computing, Web-based collaborative learning has become a popular research issue. Many researchers have paid attention on discussion of how instructors can efficiently to plan and organize classroom teaching activities and strategies based on a cloud environment. In this thesis, we aimed at exploring the effects of Web-based collaborative learning on students' learning achievement, retentions, and attitudes on curriculum social studies by using Google cloud services. We used quasi-experimental method as our research design and recruited 54 students who are sixth grade from an elementary school in Taichung city as research objects. Each student was assigned to an experimental group or a control group according to his/her original class. The experimental group will be treated with the Web-based collaborative learning, while the control group is given the traditional didactic instruction. The experimental result shows that participants of different groups had significantly different levels of “learning achievement”, “learning retentions” and “learning attitudes”. Through the investigation of using Google cloud services for Web-based collaborative learning on experimental group, most students had positive attitude and high acceptance of Google cloud services. According to these findings, we conclude that using Google cloud services as Web-based collaborative learning tools is helpful on curriculum social studies.
21
Sabih, Rafia. "Balancing Money and Time for OLAP Queries on Cloud Databases." Thesis, 2016. http://etd.iisc.ac.in/handle/2005/2931.
Full textAbstract:
Enterprise Database Management Systems (DBMSs) have to contend with resource-intensive and time-varying workloads, making them well-suited candidates for migration to cloud plat-forms { specifically, they can dynamically leverage the resource elasticity while retaining affordability through the pay-as-you-go rental interface. The current design of database engine components lays emphasis on maximizing computing efficiency, but to fully capitalize on the cloud's benefits, the outlays of these computations also need to be factored into the planning exercise. In this thesis, we investigate this contemporary problem in the context of industrial-strength deployments of relational database systems on real-world cloud platforms.
Specifically, we consider how the traditional metric used to compare query execution plans, namely response-time, can be augmented to incorporate monetary costs in the decision process. The challenge here is that execution-time and monetary costs are adversarial metrics, with a decrease in one entailing a rise in the other. For instance, a Virtual Machine (VM) with rich physical resources (RAM, cores, etc.) decreases the query response-time, but is expensive with regard to rental rates. In a nutshell, there is a tradeoff between money and time, and our goal therefore is to identify the VM that others the best tradeoff between these two competing considerations. In our study, we pro le the behavior of money versus time for a given query, and de ne the best tradeoff as the \knee" { that is, the location on the pro le with the minimum Euclidean distance from the origin.
To study the performance of industrial-strength database engines on real-world cloud infrastructure, we have deployed a commercial DBMS on Google cloud services. On this platform, we have carried out extensive experimentation with the TPC-DS decision-support benchmark, an industry-wide standard for evaluating database system performance. Our experiments demonstrate that the choice of VM for hosting the database server is a crucial decision, because: (i) variation in time and money across VMs is significant for a given query, (ii) no one VM offers the best money-time tradeoff across all queries.
To efficiently identify the VM with the best tradeoff from a large suite of available configurations, we propose a technique to characterize the money-time pro le for a given query. The core of this technique is a VM pruning mechanism that exploits the property of partially ordered set of the VMs on their resources. It processes the minimal and maximal VMs of this poset for estimated query response-time. If the response-times on these extreme VMs are similar, then all the VMs sandwiched between them are pruned from further consideration. Otherwise, the already processed VMs are set aside, and the minimal and maximal VMs of the remaining unprocessed VMs are evaluated for their response-times. Finally, the knee VM is identified from the processed VMs as the one with the minimum Euclidean distance from the origin on the money-time space. We theoretically prove that this technique always identifies the knee VM; further, if it is acceptable to and a \near-optimal" knee by providing a relaxation-factor on the response-time distance from the optimal knee, then it is also capable of finding more efficiently a satisfactory knee under these relaxed conditions.
We propose two favors of this approach: the first one prunes the VMs using complete plan information received from database engine API, and named as Plan-based Identification of Knee (PIK). On the other hand, to further increase the efficiency of the identification of the knee VM, we propose a sub-plan based pruning algorithm called Sub-Plan-based Identification of Knee (SPIK), which requires modifications in the query optimizer.
We have evaluated PIK on a commercial system and found that it often requires processing for only 20% of the total VMs. The efficiency of the algorithm is further increased significantly, by using 10-20% relaxation in response-time. For evaluating SPIK , we prototyped it on an open-source engine { Postgresql 9.3, and also implemented it as Java wrapper program with the commercial engine. Experimentally, the processing done by SPIK is found to be only 40% of the PIK approach.
Therefore, from an overall perspective, this thesis facilitates the desired migration of enterprise databases to cloud platforms, by identifying the VM(s) that offer competitive tradeoffs between money and time for the given query.
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Sabih, Rafia. "Balancing Money and Time for OLAP Queries on Cloud Databases." Thesis, 2016. http://etd.iisc.ernet.in/handle/2005/2931.
Full textAbstract:
Enterprise Database Management Systems (DBMSs) have to contend with resource-intensive and time-varying workloads, making them well-suited candidates for migration to cloud plat-forms { specifically, they can dynamically leverage the resource elasticity while retaining affordability through the pay-as-you-go rental interface. The current design of database engine components lays emphasis on maximizing computing efficiency, but to fully capitalize on the cloud's benefits, the outlays of these computations also need to be factored into the planning exercise. In this thesis, we investigate this contemporary problem in the context of industrial-strength deployments of relational database systems on real-world cloud platforms.
Specifically, we consider how the traditional metric used to compare query execution plans, namely response-time, can be augmented to incorporate monetary costs in the decision process. The challenge here is that execution-time and monetary costs are adversarial metrics, with a decrease in one entailing a rise in the other. For instance, a Virtual Machine (VM) with rich physical resources (RAM, cores, etc.) decreases the query response-time, but is expensive with regard to rental rates. In a nutshell, there is a tradeoff between money and time, and our goal therefore is to identify the VM that others the best tradeoff between these two competing considerations. In our study, we pro le the behavior of money versus time for a given query, and de ne the best tradeoff as the \knee" { that is, the location on the pro le with the minimum Euclidean distance from the origin.
To study the performance of industrial-strength database engines on real-world cloud infrastructure, we have deployed a commercial DBMS on Google cloud services. On this platform, we have carried out extensive experimentation with the TPC-DS decision-support benchmark, an industry-wide standard for evaluating database system performance. Our experiments demonstrate that the choice of VM for hosting the database server is a crucial decision, because: (i) variation in time and money across VMs is significant for a given query, (ii) no one VM offers the best money-time tradeoff across all queries.
To efficiently identify the VM with the best tradeoff from a large suite of available configurations, we propose a technique to characterize the money-time pro le for a given query. The core of this technique is a VM pruning mechanism that exploits the property of partially ordered set of the VMs on their resources. It processes the minimal and maximal VMs of this poset for estimated query response-time. If the response-times on these extreme VMs are similar, then all the VMs sandwiched between them are pruned from further consideration. Otherwise, the already processed VMs are set aside, and the minimal and maximal VMs of the remaining unprocessed VMs are evaluated for their response-times. Finally, the knee VM is identified from the processed VMs as the one with the minimum Euclidean distance from the origin on the money-time space. We theoretically prove that this technique always identifies the knee VM; further, if it is acceptable to and a \near-optimal" knee by providing a relaxation-factor on the response-time distance from the optimal knee, then it is also capable of finding more efficiently a satisfactory knee under these relaxed conditions.
We propose two favors of this approach: the first one prunes the VMs using complete plan information received from database engine API, and named as Plan-based Identification of Knee (PIK). On the other hand, to further increase the efficiency of the identification of the knee VM, we propose a sub-plan based pruning algorithm called Sub-Plan-based Identification of Knee (SPIK), which requires modifications in the query optimizer.
We have evaluated PIK on a commercial system and found that it often requires processing for only 20% of the total VMs. The efficiency of the algorithm is further increased significantly, by using 10-20% relaxation in response-time. For evaluating SPIK , we prototyped it on an open-source engine { Postgresql 9.3, and also implemented it as Java wrapper program with the commercial engine. Experimentally, the processing done by SPIK is found to be only 40% of the PIK approach.
Therefore, from an overall perspective, this thesis facilitates the desired migration of enterprise databases to cloud platforms, by identifying the VM(s) that offer competitive tradeoffs between money and time for the given query.
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LI, Hao-Wei, and 李浩維. "The Cloud Computing and Service based on Google App Engine." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/98436870504430546245.
Full textAbstract:
碩士嶺東科技大學
數位媒體設計研究所
98
The cloud computing is overthrowing the former ones completely nowadays. No mater how complicated the computer science is, the cloud computing service can be even more boundless with the combination of computers and network. To catch the trade of cloud computing, Google provides a series of service such as Google Calendar, Good Docs, and Google Sites. Google is the most enthusiastic impetus company in order to promote cloud computing. Google App Engine is the basic framework for constructing the idea of cloud computing. Through developing the applications by Google App Engine, the concept of “software equals to service” will come into existence. Google App Engine also provides applications which are based on cloud computing structure with more convenient and direct manners. Moreover, Google App Engine can be integrated with all the API for expanding the specific need. Through documentary analysis, this project will employ Google App Engine into a program, so that one can compare and define the effect with different server sites and cloud computing service sites. The ultimate effort of this project is to develop a simple WebPOS cloud computing application program to present and prove the whole research idea.
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Ting, Yu-Hsuan, and 丁于軒. "A Study on the Use of Google Cloud Service on Cross Device." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/ytnnz2.
Full textAbstract:
碩士國立臺灣師範大學
科技應用與人力資源發展學系
105
This study aims to explore user acceptance of cross-device Google Cloud service in understanding their continuance intention to use the service on computer, smart phone and tablet. The study was conducted based on Post-Acceptance Model of IS Continuance and combined with system quality from IS Success Model. Then, a user feedback questionnaire for college students and office workers was conducted further to evaluate acceptance. The analytic results showed that user confirmation of using cross-device Google Cloud service contributed significantly to perceived usefulness. Confirmation and system quality had positive effect on satisfaction, respectively while satisfaction had positive effect on continuance intention. In addition, the findings on analyzing users in different societies were as follows: in college students group, the female students with two devices got higher average score in each aspect while the male students with three devices got higher average score; in office workers group, the young workers (under the age of 34) were significantly with higher perceived usefulness than the elder workers (above the age of 34), and the young workers with two devices got higher average score in each aspect while the elder workers with three devices got higher average score. Finally, this study is expected to provide insight on cloud usage for cloud service developing, cross-device marketing, and teaching with technology.
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陳漢峻, Han-Chun Chen, and 陳漢峻. "Design and Implementation of Smart Bike applications based on Google Map Cloud Service." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/9xbgk2.
Full textAbstract:
碩士淡江大學
資訊工程學系碩士在職專班
103
In recent years, mobile phone manufacturers have launched smart phones primarily, but Google also launched a Android smartphone operating system, and Android operating system and provides an open mobile platforms. Many sites have special web services, and other services such as Google Map. However, when the user wants to use the service provided by different sites, you can mix and match the way through the integration of these services, to produce the services they need. The study is based on Google Map as a service platform, then combine Smart-Bike implement cloud services Google Map application, partly by GPS positioning data, humidity, CO2, noise, temperature, etc. as do MySQL database and data integration stored for future integration of other applications and data correlation process. Information disclosure we have established in the Android Mashup Engine to match a Google Map data, and then do the processing through data on MySQL, and Smart-Bike Information Technology to Google Maps API to provide map services, and through a web platform will be consolidated as the future of information application queries.
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Chang, Wei-Hsuan, and 張維軒. "Studies on Cloud Computing Service - A Case Study of Applying Google Map on Tel-Home Care." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/46337132752721082716.
Full textAbstract:
碩士淡江大學
資訊管理學系碩士班
98
In 2008 our government announced that Tel-Home Care is one of the new type of industry service. The purpose of Tel-Home Care is to take care of cared patients continuously even when they at home. The care workers can take care of them through the Tel-medical information system, but there are some tasks that care workers must pay a visit to patients by themselves, for instance, rehabilitation and meal delivery, thus, care workers have to go to a lot of place when they run their tasks. So we must plan the routing path and visiting order well. Planning the routing path is a Traveling Salesman Problem, there were some researches propose some methods to solve it, for instance, Ant Algorithm, Tabu Search and Genetic Algorithms. To plan the routing path, we must get geographical information in the real world. Fortunately, the Google company released geographical information on its cloud computing service know as Google Map, we can get its service easily only through its JavaScript API. So, we attempt to combine Google Map service with Traveling Salesman Problem and applying it on Tel-Home Care. We implement a system whitch help care workers to plan visiting order, path and estimated arrival time for each cared patients. Our System can be divided into two parts, one is Geographical Information Processing Module which communicates with the Google Map service to get geographical information in the real world and send data to the other part, we call it routing path planning module. When it receives the data from geographical information processing module, it assigns nodes and computes routing paths and estimated service intervals for each care worker. Then it returns the processed results to the geographical information processing module for displaying. Finally, we demonstrate the architecture and instructions of our system.
27
Fan, Kang-Lun, and 范綱倫. "Fuzzy C-means Clustering Method is Applied to the Wireless Base Station Clustering in the Google Maps Cloud Service Area." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/86667215645931331132.
Full textAbstract:
碩士國立中央大學
通訊工程研究所碩士在職專班
100
Google maps latitude is usually learned through the Global Positioning System (GPS) coordinates of the current, but the exact error rate of about 3 to 5 meters, while the GPS signals penetrate the problem of insufficient thick clouds, or positioning place a larger shelter, the positioning effect will be poor positioning time will be longer, if into your living room or tunnel, the GPS is useless, a lot of literature has been exploring the use of WiFi to do positioning feasibility, when the user opens a WiFi mobile devices, mobile devices, proactive detection around the wireless network base station, as long as the search to three or more base station signals, and signal strength (RSSI) and three point positioning method , we can calculate the actual location of the positioning accuracy better than the GPS to the wireless base stations deployed in the metropolitan area is quite dense, making our lives around us is full of the signal of the wireless base station positioning speed GPS to fast on many. Using WiFi to complete positioning, the principle as mentioned above, these wireless base units are usually placed in a fixed position, grasp the location of the AP, and the establishment of a database, first the clustering of the wireless base station in the region, rapid screening available wireless base station signal, I believe there will be a real help for shortening the time of the cloud computing Therefore, this thesis combined with the implementation of the Google Maps API, and the application of fuzzy clustering method, the actual simulation area wireless base station signal in the region to complete the clustering of wireless base stations, to reduce the time of cloud computing.