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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
821

Právní aspekty cloud computingu: GaaS (gaming as a service) jako nová forma cloudové služby / Law aspect of cloud computing: GaaS as a new form of cloud servis

Janda, Petr January 2021 (has links)
Cloud gaming, also known as Gaming as a Service or GaaS is a quickly developing service with significant economic potential. Author follows this trend and focuses on the topic of providing videogames as a service through cloud environment. The goal of this work was to analyse and describe legal relations between authors of videogames, providers, and users of GaaS in the context of Czech copyright and to present practical consequences of these relations, mainly in contrast to SaaS. Firstly, the reader is acquainted with basic aspects of videogames with emphasis on classification and description of videogames and its parts, i.e. computer program and other elements, as a work of authorship. Author describes possible theoretical views on the protection of audio-visual components of videogames. It is then pointed out that no satisfactory classification of video game as a singular work of authorship can be provided under the Czech Copyright Act. Videogame legislation is also proposed. Subject of the second section of this thesis is cloud gaming technology. This segment is written as to be understandable even for non-experts in the field. At first basic types of cloud services are presented. Then, the technology behind cloud gaming is described, along with business models one can come across nowadays....
822

Desarrollo de un modelo de BI & Analytics usando infraestructura Cloud para la Gestión de PMO en una consultora de TI / Development of a BI & Analytics model using Cloud infrastructure for PMO Management in an IT consultancy

Cayllahua Huaman, Erick Eduardo, Ramos Arias, Felipe Anthonino 12 August 2020 (has links)
El presente proyecto de tesis tiene como objetivo analizar, diseñar y modelar la arquitectura software para el proceso de gestión de PMO. Este modelo arquitectural será utilizado como base de soporte a los procesos de gestión de llamadas y tickets de la consultora de TI “NECSIA”. La finalidad del presente proyecto es resolver la situación problemática del proceso mencionado que será parte de un análisis profundo la cual se detallará más adelante. El punto crítico de esta situación problemática es que muchas actividades de extracción, transformación y homologación de datos se realizan de manera manual, lo que impide una correcta centralización del flujo de datos en la empresa. El presente proyecto propone una solución de BI y Analytics donde se destaca el modelo arquitectural 4C que integrará las diversas fuentes de información en un repositorio unificado en Cloud. Por tal motivo, se podrá obtener una adecuada gestión y gobierno de datos, sobre todo en sus cálculos históricos de los proyectos involucrados en el proceso de Gestión de PMO. En este contexto, el documento a presentar plantea el uso del marco de trabajo Zachman para en realizar un análisis profundo del negocio con la finalidad de alinear el proceso evaluado a los objetivos estratégicos del negocio. En cuanto respecta al diseño del Modelado de los procesos de negocio se utilizó la notación BPMN. Este estándar nos permitirá mejorar la descomposición y modularización de las actividades que se involucran en los procesos. Finalmente, la presente solución de BI & Analytics busca ser parte del cambio continuo y estar alineados a los objetivos estratégicos de la empresa. / This thesis project aims to analyze, design and model the software architecture for the PMO management process. This architectural model will be used as a support base for the call and ticket management processes of the IT consultancy “NECSIA”. The purpose of this project is to solve the problematic situation of the mentioned process that will be part of an in-depth analysis which will be detailed later. The critical point of this problematic situation is that many data extraction, transformation and homologation activities are carried out manually, which prevents a correct centralization of the data flow in the company. This project proposes a BI and Analytics solution that highlights the 4C architectural model that will integrate the various sources of information in a unified repository in the Cloud. For this reason, adequate data management and governance can be obtained, especially in its historical calculations of the projects involved in the PMO Management process. In this context, the document to be presented proposes the use of the Zachman framework to carry out an in-depth analysis of the business in order to align the evaluated process with the strategic objectives of the business. Regarding the design of the Business Process Modeling, the BPMN notation was used. This standard will allow us to improve the decomposition and modularization of the activities that are involved in the processes. Finally, the present BI & Analytics solution seeks to be part of the continuous change and be aligned with the strategic objectives of the company. / Tesis
823

Predictive model based on sentiment analysis for peruvian smes in the sustainable tourist sector

Zapata, Gianpierre, Murga, Javier, Raymundo, Carlos, Alvarez, Jose, Dominguez, Francisco 01 January 2017 (has links)
In the sustainable tourist sector today, there is a wide margin of loss in small and medium-sized enterprise (SMEs) because of a poor control in logistical expenses. In other words, acquired goods are note being sold, a scenario which is very common in tourism SMEs. These SMEs buy a number of travel packages to big companies and because of the lack of demand of said packages, they expire and they become an expense, not the investment it was meant to be. To solve this problem, we propose a Predictive model based on sentiment analysis of a social networks that will help the sales decision making. Once the data of the social network is analyzed, we also propose a prediction model of tourist destinations, using this information as data source it will be able to predict the tourist interest. In addition, a case study was applied to a real Peruvian tourist enterprise showing their data before and after using the proposed model in order to validate the feasibility of proposed model.
824

Up in the Cloud : Exploring small and medium-sized enterprises cloud computing adoption factors

Ljungberg, Cajsa, Olsson, Sara January 2021 (has links)
Background: The intense growth of data that is continuously expanding has resulted in SMEs using cloud computing to store, process and analyze data. Thus, a critical element is for SMEs to understand the value of cloud computing and the factors influencing the adoption decision.  Problem: Due to the increased use of cloud computing, the importance of examining the factors that can affect and impact SMEs adoption has been highlighted. Cloud computing has been pointed out as a component for SMEs to stay competitive and sustainable in public crises and uncertain environments. Despite the importance among scholars, no research has studied cloud adoption factors among SMEs during 2020 - 2021 and the present of a public crisis. Purpose: The purpose of this research is to investigate and explore SMEs cloud computing adoption factors in the turbulent time of a public crisis. The result of this research is expected to add knowledge and theoretical insights to existing literature and fill the gap within the underexplored context of cloud computing adoption factors during public crisis. Method: In this research, a qualitative research design was applied where six semi-structured interviews with people experienced of the phenomenon under study were conducted and eight customer cases with cloud users were collected from cloud providers' websites. Conclusion: The findings of this research declared ten significantly important factors; complexity, compatibility, relative advantage, cost savings, security, top management support, technology readiness, organizational culture, competition and trading partner pressure and supplier computing support, to influence SMEs cloud computing adoption. Although this research was conducted during the time of a public crisis, no conclusion of the crisis' impact on which factors influencing SMEs cloud computing adoption could be recognized.
825

Functional Decomposition Techniques and Their Impact on Performance, Scalability and Maintainability

van Dreven, Jonne January 2021 (has links)
Context The last decade shows many solution proposals of functional decomposition techniques to aid in developing microservice architectures. While some solutions may work, it is uncertain what the effects are on quantitative, measurable metrics; thus, the proposals require validation. Objective The study measures the effects of various functional decomposition techniques on performance, scalability, and maintainability. Furthermore, the study will compare the treatments in order to find whether a statistical significance exists. Method The study uses a controlled experiment containing three functional decomposition techniques—Event Storming, Actor/Action, and Service Cutter—applied on the same use case. The use case follows the CoCoMe framework, which forms the basis of the experiment. Results Each treatment shows similar behavior while presenting different architectural designs. The study found no statistical significance for performance, scalability, and maintainability. Conclusion Evidence suggests that the convenience of an approach might be more important than the resulting architecture since they will likely lead to the same outcome. If performance issues arise, it would likely be due to the microservices architecture and not the functional decomposition technique; therefore, the microservices architecture might not equally benefit any situation or corporation. Furthermore, the study found that service granularity might not be as relevant as some studies claim it to be, and other factors could be more crucial.
826

Comparison of GCP and AWS using usability heuristic and cognitive walkthrough while creating and launching Virtual Machine instances in VirtualPrivate Cloud

Cherukuri, Prudhvi Nath Naidu, Ganja, Sree Kavya January 2021 (has links)
ABSTRACT Cloud computing has become increasingly important over the years, as the need for computational resources, data storage, and networking capabilities in the field of information technology has been increased. There are several large corporations that offer these services to small companies or to end-users such as GCP, AWS, Microsoft Azure, IBM Cloud, and many more. The main aim of this thesis is to perform the comparison of GCP and AWS consoles in terms of the user interface while performing tasks related to compute engine. The cognitive walkthrough has been performed on tasks such as the creation of VPC, creation of VM instances, and launching them and then from the results, both the interfaces are compared using usability heuristics. Background: As the usage of cloud computing has increased over the years, the companies that are offering these services have grown eventually. Though there are many cloud services available in the market the user might always choose the services that are more flexible and efficient to use. In this manner, the choice of our research is made to compare the cloud services in terms of user interaction user experience. As we dig deep into the topic of user interaction and experience there are evaluation techniques and principles such as cognitive walkthrough and usability heuristics are suitable for our research. Here the comparison is made among GCP and AWS user interfaces while performing some tasks related to compute engine. Objectives: The main objectives of this thesis are to create VPC, VM instances,s and launch VM instances in two different cloud services such as GCP and AWS. To find out the best user interface among these two cloud services from the perspective of the user. Method: The process of finding best user interface among GCP and AWS cloud services is based on the cognitive walkthrough and comparing with usability heuristics. The cognitive walkthrough is performed on chosen tasks in both the services and then compared using usability heuristics to get the results of our research. Results: The results that are obtained from cognitive walkthrough and comparison with usability heuristics shown in graphical formats such as bar graphs, pie charts, and the comparison results are shown in the form of tabular form. The results cannot be universal, as they are just observational results from cognitive walkthrough and usability heuristic evaluation. Conclusion: After performing the above-mentioned methods it is observed that the user interface of GCP is more flexible and efficient in terms of user interaction and experience. Though the user experience may vary based on the experience level of users in cloud services, as per our research the novice user and moderate users have chosen GCP as a better interactive system over AWS. Keywords: Cloud computing, VM instance, Cognitive walkthrough, Usability heuristics, User-interface.
827

Přínosy a problémy využití cloud computingu ve státní správě, informačních institucích a knihovnách / Cloud Computing in Public Sector - Benefits and Risks

Rejnek, Tomáš January 2015 (has links)
(anglicky) This thesis deals with benefits and risks of using cloud computing in public sector institutions. The thesis focuses mainly on the usage of public cloud deployment model. The thesis is divided into 4 main chapters. The first chapter presents definition and basic characteristics of cloud computing. The second part consists of PESTL analysis that describes the impact of macro-environmental factors (namely political, economical, social, technological and legal factors) on the use of cloud computing in public sector institutions. The third part presents SWOT analysis of cloud computing and its use in public sector. The fourth chapter presents a case study of the implementation of cloud computing services at The Faculty of Arts of the Charles University. The results of the conducted analysis tend to positive effects of cloud computing use in public sector institutions, presuming a proper risk analysis is done before implementation begins. Klíčová slova (anglicky): Cloud computing, IaaS, PaaS, SaaS, public sector, PESTL, SWOT, virtualisation
828

Digital forensics - Performing virtual primary memory extraction in cloud environments using VMI

Hjerpe, David, Bengtsson, Henrik January 2018 (has links)
Infrastructure as a Service and memory forensics are two subjects which have recently gained increasing amounts of attention. Combining these topics poses new challenges when performing forensic investigations. Forensics targeting virtual machines in a cloud environment is problematic since the devices are virtual, and memory forensics are a newer branch of forensics which is hard to perform and is not well documented. It is, however an area of utmost importance since virtual machines may be targets of, or participate in suspicious activity to the same extent as physical machines. Should such activity require an investigation to be conducted, some data which could be used as evidence may only be found in the primary memory. This thesis aims to further examine memory forensics in cloud environments and expand the academic field of these subjects and help cloud hosting organisations. The objective of this thesis was to study if Virtual Machine Introspection is a valid technique to acquire forensic evidence from the virtual primary memory of a virtual machine. Virtual Machine Introspection is a method of monitoring and analysing a guest via the hypervisor. In order to verify whether Virtual Machine Introspection is a valid forensic technique, the first task was to attempt extracting data from the primary memory which had been acquired using Virtual Machine Introspection. Once extracted, the integrity of the data had to be authenticated. This was done by comparing a hash sum of a file located on a guest with a hash sum of the extracted data. The experiment showed that the two hashes were an exact match. Next, the solidity of the extracted data was tested by changing the memory of a guest while acquiring the memory via Virtual Machine Introspection. This showed that the solidity is heavily compromised because memory acquisition process used was too slow. The final task was to compare Virtual Machine Introspection to acquiring the physical memory of the host. By setting up two virtual machines and examining the primary memory, data from both machines was found where as Virtual Machine Introspection only targets one machine, providing an advantage regarding privacy.
829

Mocking SaaS Cloud for Testing

Svensgård, Simon, Henriksson, Johannes January 2017 (has links)
In this paper we evaluate how software testing is affected by the usage of a mock-object, a dummy implementation of a real object, in place of having data in a cloud that is accessed through an API. We define the problems for testing that having data in the cloud brings, which of these problems a mock-object can remedy and what problems there are with testing using the mock-object. We also evaluate if testing using the mock-object can find the same faults as testing against the cloud and if the same code can be covered by the tests. This is done at Blekinge Institute of Technology(BTH) by creating an integration system for the company Cybercom Sweden and Karlskrona Municipality. This integration system is made in C# and works by syncing schedules from Novaschem to a cloud service, Google Calendar. With this paper we show that a mock-object in place of a cloud is very useful for testing when it comes to clean-up, triggering certain states and to avoid query limitations. / I detta arbete utvärderar vi hur programvarutestning påverkas av användandet av ett mock-objekt, en dummy-implementation av ett riktigt objekt, istället för att ha data i ett moln som man kommer åt via ett API. Vi definierar de problem som uppkommer av att ha data i molnet, vilka problem som kan avhjälpas av mock-objektet och vilka problem mock-objektet medför. Vi utvärderar även om testning med ett mock-objekt kan finna samma fel som testning mot molnet och om samma kod kan täckas av testerna. Detta görs på Blekinge Tekniska Högskola(BTH) genom att skapa ett integrationssystem för företaget Cybercom Sweden och Karlskrona Kommun. Integrationssystemet görs i C# och fungerar som så att det synkar scheman från Novaschem till en molntjänst, Google Calendar. Med detta arbete visar vi att ett mock-objekt istället för molnet är väldigt användbart när det kommer till städning efter tester, att utlösa vissa tillstånd och för att undvika begränsningar.
830

Improving the Response Time of M-Learning and Cloud Computing Environments Using a Dominant Firefly Approach

Sekaran, Kaushik, Khan, Mohammad S., Patan, Rizwan, Gandomi, Amir H., Krishna, Parimala Venkata, Kallam, Suresh 01 January 2019 (has links)
Mobile learning (m-learning) is a relatively new technology that helps students learn and gain knowledge using the Internet and Cloud computing technologies. Cloud computing is one of the recent advancements in the computing field that makes Internet access easy to end users. Many Cloud services rely on Cloud users for mapping Cloud software using virtualization techniques. Usually, the Cloud users' requests from various terminals will cause heavy traffic or unbalanced loads at the Cloud data centers and associated Cloud servers. Thus, a Cloud load balancer that uses an efficient load balancing technique is needed in all the cloud servers. We propose a new meta-heuristic algorithm, named the dominant firefly algorithm, which optimizes load balancing of tasks among the multiple virtual machines in the Cloud server, thereby improving the response efficiency of Cloud servers that concomitantly enhances the accuracy of m-learning systems. Our methods and findings used to solve load imbalance issues in Cloud servers, which will enhance the experiences of m-learning users. Specifically, our findings such as Cloud-Structured Query Language (SQL), querying mechanism in mobile devices will ensure users receive their m-learning content without delay; additionally, our method will demonstrate that by applying an effective load balancing technique would improve the throughput and the response time in mobile and cloud environments.

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