Popularity Of Cloud Services Research Articles

Implementation of cloud computing in the digital accounting system of logistics companies

The aim of the article is to determine the capabilities of cloud services for meeting the needs of logistics companies in the management of supply chains and digital accounting. The study provides a review of current academic publications, analysis of official documentation of cloud service provider companies, and expert opinion of the authors of the study. The study was based on information about the 5 most popular cloud services used by companies to perform mathematical calculations. Amazon Web Services focus on reliability and scalability, providing a wide range of data storage and processing services, as well as performing serverless mathematical calculations. Microsoft Azure stands out for its integrated solutions, as well as data management and analytics services. Google Cloud offers a wide range of development and analytics tools, including data visualization and data sharing. Oracle Cloud provides comprehensive financial and database management solutions. SAP Cloud Platform specializes in financial management and analytics solutions. The results of the research open up prospects for studying the problems of integrating services built on different platforms and finding optimal solutions for combining the existing system of mathematical calculations in a logistics company with the offered cloud-based services.

Integration of cloud technologies into virtual reality

Investigated the possibilities of integrating cloud technologies into virtual reality in order to further improve software tools and increase its efficiency and accessibility. Analysed architectural and infrastructure solutions for the use of cloud services, processing and storage of large data in virtual environments. Conducted a comprehensive scientific study of the possibilities of integrating cloud technologies into virtual reality in order to increase the efficiency and accessibility of this technological segment. Studied the challenges that arise when integrating cloud technologies, in particular, the problems of delays in data transmission and measures to ensure security and privacy in cloud environments. Considered the necessity of developing a cloud infrastructure in popular cloud services, in particular, Amazon Web Services (AWS), to optimise computing tasks and increase overall efficiency, as well as the possibility of scaling virtual reality technology. Article considers the possibility of creating a solution for interacting with cloud resources and using virtual reality applications. The services of a cloud provider are used to allocate computing resources, create a data warehouse, create and manage a virtual network, install and configure solutions for deploying and configuring server software components, and conduct an experiment. Evaluated the impact of cloud technology integration on the quality and availability of virtual reality, and provide prospects for the development of this association. In addition, considered the possibilities of creating optimised solutions for interacting with cloud resources and using virtual reality applications, and assessed the impact of cloud integration on the quality and availability of virtual reality. Developed a software solution and approach for building a cloud infrastructure, described in detail all the steps of creating and deploying a virtual server and data storage for its interaction with virtual reality systems. Prospects for the development of such an association open up wide horizons for innovative technologies in the information technology segment. The results of the study can become an important source of relevant strategic information for further improvement of cloud-virtual environments and development of innovative technologies in the information technology segment.

ASSESSING THE EFFICACY OF CLOUD SERVICES FOR DEVELOPING EDUCATIONAL PRESENTATIONS

The article examines the most popular cloud services for creating educational presentations and seeks to determine the effectiveness of their integration within the educational framework. A webometric analysis of these cloud services resulted in the identification of the top 10 resources commonly employed for presentation creation, including Prezi, Sway, Slides, PowToon, Canva, ZohoShow, Genial.ly, Emaze, Piktochart, VideoScribe, among others. Our research conducted a comprehensive comparative analysis of these platforms, utilizing web analytics tools such as Ahrefs, Moz, and Similarweb to establish their respective rankings. This approach facilitated an encompassing selection of cloud-based educational tools capable of meeting the multifaceted requirements of all stakeholders in the educational process. The analytical process unfolded across multiple stages: an initial description and assessment of key parameters of each cloud service, subsequent expert evaluations encompassing both parameter specifics and overall service quality, determination of individual parameter impact coefficients on service efficiency, service evaluations based on specific parameters, and a synthesis of both objective and subjective data to summarize outcomes. In-depth analysis was conducted on the presentation creation features inherent to each cloud service, leading to the identification of evaluation parameters encompassing functionality, usability, cost-effectiveness, unique attributes, and overall user impression. Each parameter was assigned an impact factor to gauge its significance within the overall assessment of a given cloud service. The culmination of expert evaluations culminated in the recognition of Prezi, Canva, and Google Slides as highly effective tools. This determination is grounded in their extensive functionality, provision of free accounts, and user-friendly interfaces. Analysis of domain ratings further highlighted the popularity of Sway, Canva, and Prezi, underscoring the pronounced demand for these platforms among users. The evaluation methodology proposed within this study holds potential for application to other cloud services designed for educational content creation. By fostering effective organization of educational activities across diverse subject domains, this approach contributes to the enhancement of the educational process as a whole.

Performance Analysis and Comparison of the Micro Virtual Machines Provided by the Top Cloud Vendors.

Public Clouds are the backbone of the modern IT Industry. The modern tech start-ups to are heavily dependent on the Public Clouds as save the capital expenditure. Public Clouds offer a wide range of Virtual Infrastructure beginning from single core 0.25 GB RAM virtual machines to 128 cored 3904 GB RAM Virtual Servers aided with GPUs. Apart from costing, The performance of the virtual machines can impact on the services offered. The paper tries to analyse the performance of the Light virtual machines provided by the different cloud vendors and maps their ability to handle certain set of tasks. The prime objective is to compare the entry level virtual machines that are mostly used across the industry for the multiple purposes and find which is the efficient and productive. The systems under Test are the 1 GB RAM machines provided by the most popular Cloud service providers.

Application of cloud technologies in mathematics learning process

The article highlights the main possibilities of using cloud technologies in the process of teaching mathematics; popular cloud services that are used in the teacher’s work.

Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT

Conventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially in the fault monitoring and normalizing fields in distribution systems. This paper introduces smart fault monitoring and normalizing technologies in distribution systems by using one of the most popular cloud service platforms, the Microsoft Azure Internet of Things (IoT) Hub, together with some of the related services. A hardware prototype was constructed based on part of a real underground distribution system network, and the fault monitoring and normalizing techniques were integrated to form a system. Such a system with IoT integration effectively reduces the power outage experienced by customers in the healthy section of the faulted feeder from approximately 1 h to less than 5 min and is able to improve the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in electric utility companies significantly.

Analysis of modern cloud services to ensure cybersecurity

This article describes the use of cloud services. The analysis of the most popular cloud services and comparison of their basic functionality is carried out. Examples of practical application of cloud services among well-known companies around the world are given. Basic recommendations to secure access organization to cloud-based services are presented.

Model of the location system for transport

In the modern world, tracking systems are actively implemented in various forms, ranging from smart surveillance cameras and integrated smart home systems to tracking parcels, passenger vehicles or vehicles carrying important cargo. This topic is actual for the companies working with vehicles, such as insurance companies, emergency services, and car fleets where tracking the vehicles becomes the commercial necessity. It also concerns those who prefer to work on a rotational basis and have contractors on wheels, for example mining companies, where it is important to track accurately the location of vehicles and calculate the route time. The tracker is a small device used to determine the location and track it. Nowadays, due to its unique properties, this device has a wide range of implementations such as monitoring of children and the elderly, creating optimal routes for the movement of goods using car navigators and video recorders, or ensuring the safety and accuracy of movement of private and commercial vehicles. These small electronic devices can not only determine their coordinates using GPS satellites, but use the built-in communication module to send them to a remote server for further database storage and processing. The currently popular cloud services can be used as a remote server, for instance, Amazon Web Services, the computing power of which is distributed in many geographic locations all around the world, and therefore, it is possible not only to save the obtained data in the geographic location closest to the user, but also to perform their analysis and processing without renting a separate physical server.

Operation and maintenance(O&M) for data center: An intelligent anomaly detection approach

With the popularity of cloud services and big data in the Internet enterprise, the operation and maintenance (O&M) of data centers have become more critical. The key to O&M is to find anomalies through indicator data. However, the traditional O&M suffers from poor efficiency and low satisfaction, along with a low degree of intelligence. Therefore, introducing a machine learning based anomaly detection method in O&M can effectively improve real-time detection accuracy and make O&M more intelligent. Based on two typical O&M problems prevalent in Internet enterprises at present, stability detection and unattended release of cluster machines, this paper proposes an intelligent anomaly detection approach, called Ensemble learning on Partition Interval (ELPI). The main steps include dividing the data set into the stable interval and the unsteady interval. Then we establish an online/offline algorithm module and perform corresponding integrated learning for different interval characteristics to detect abnormal data. At last, we set up a self-feedback mechanism to dynamically adjust the module threshold. The results show that our method is more accurate and stable than traditional methods. Additionally, our method has been effectively applied to the anomaly detection of big clusters and app release.

Integration of NLP and Speech-to-text Applications with Chatbots

With the evolving artificial intelligence technology, the chatbots are becoming smarter and faster lately. Chatbots are typically available round the clock providing continuous support and services. A chatbot or a conversational agent is a program or software that can communicate using natural language with humans. The challenge of developing an intelligent chatbot still exists ever since the onset of artificial intelligence. The functionality of chatbots can range from business oriented short conversations to healthcare intervention based longer conversations. However, the primary role that the chatbots have to play is in understanding human utterances in order to respond appropriately. To that end, there is an increased emergence of Natural Language Understanding (NLU) engines by popular cloud service providers. The NLU services identify entities and intents from the user utterances provided as input. Thus, in order to integrate such understanding to a chatbot, this paper presents a study on existing major NLU platforms. Then, we present a case study chatbot integrated with Google DialogFlow and IBM Watson NLU services and discuss their intent recognition performance.

Integer multiplication ranking method for cloud services selection

Several popular cloud service providers such as Microsoft, Amazon, Google and others are competing to provide fast, reliable and efficient cloud services to the customers. Cloud computing has changed the cyber world by offering infrastructure and application services with rental charges. The decision making problem arises when selection has to be done amongst a wide range of available cloud service providers. Analytical Hierarchy Process (AHP) is a decision making method for selection amongst different options with multiple criteria. Different types of ranking methods are used in AHP which have great influence on the priorities assigned to these options. In this work, we propose an efficient and simplified ranking method named as Integer Multiplication (IM) to select the best Cloud service among the available services as per the user’s preference for different criteria and past experiences with the cloud service providers. The proposed method helps in making quick decisions as per customer’s preferences. We have demonstrated the applicability of this mechanism using a case study and also through simulated results. The results verify that the efficient and simplified proposed ranking method—“Integer Multiplication” gives accurate results for cloud service selection with reduced calculations and hence time saving in cloud service selection.

INTEGRATION OF EDUCATIONAL SUBSYSTEMS IN AN ALL-IN-ONE INFORMATION AND EDUCATION ENVIRONMENT (with open source software)

Creating an information and educational environment of a higher education institution is the process of introducing and setting up a large number of subsystems - educational, scientific, managerial and others. All these parts are largely integrated with each other. They must transfer some data to other subsystems and receive from them. In spite of the large number of works devoted to the research of creation of information and educational environments of higher educational establishments, the majority of them concern only pedagogical and organizational aspects and very few consider the issues of practical implementation with real examples. The purpose of the article is to demonstrate the technical capabilities to organizing information and educational environment through the integration of various software components. In doing so, there is a special emphasis on the use of open source elements and integration with popular cloud services. It is a difficult and expensive task to collect all the subsystems required in the educational environment of a higher education institution. The cost of complex solutions from well-known brands is measured in thousands of dollars, and their implementation requires the same integrated approach. For Ukrainian educational institutions, the solution may be to build their own information and educational environment using open source components. In most cases, such programs already have options for integrating with one another based on the same open standards. It is important to know and understand the possibilities of such integration. Its use will allow to create environment for own needs and organizational features of each institution. The possibility of gradually connecting the necessary components will make it easier to go through the process of introduction of information and educational environment and involvement of all departments of higher education in it. The examples and links in the article demonstrate the potential of open source software as an integral part of the educational environment.

FEATURES OF USING CLOUD TECHNOLOGIES IN EDUCATION

The article investigates cloud technologies and features of their use in educational institutions. The essence of cloud technologies in education is determined. It is noted that the modern institution of higher education provides usage of information and communication technologies, and in particular, cloud technologies. The main characteristics (features) which characterize cloud services are described here. It is noted that usage of cloud services has benefits and problems as well. There are such mandatory characteristics of cloud computing as self-service on demand, universal access to the network, resource pooling, elasticity, consumption accounting. Four models of deployment of cloud technologies are revealed in the article. They are corporate, public, group and hybrid. It is admitted that the most appropriate model of deployment of cloud technologies in the infrastructure of higher education institutions is hybrid. Cloud technologies support such activities as: communication, collaboration and co-operation, which determines certain areas of their usage. The architecture of cloud technologies is presented in three levels: software as a service (SaaS), platform as a service (PaaS), infrastructure as a service (IaaS). The most popular cloud services which are used in various spheres, including educational institutions, are analyzed here. Office 365, Microsoft Planner, Microsoft SkyDrive, Google Drive, Google Talk, Google Docs, these are the common cloud services which are selected in SaaS. Popular software platforms which are presented in the PaaS segment are Windows Azure, Google App Engine, Cloud9 IDE, Ideone IDE. Each of the cloud platforms that is described in the article has its own peculiarities. Possible areas of application of cloud technologies in the educational process are identified. They are free access to the programs and services used in the educational process, planning activities, implementation of the working regime of teachers and employees, the organization and conduct of scientific online conferences, seminars, forums, round tables, trainings, joint project work of students, individual independent work of students, electronic interaction with entrants.

Quantifying the Cost of Distrust: Comparing Blockchain and Cloud Services for Business Process Execution

Blockchain is of rising importance as a technology for engineering applications in cross-organizational settings, avoiding reliance on central trusted third-parties. The use of blockchain, instead of traditional databases or services, is an architectural choice in the development of a software system. Architecture impacts the non-functional qualities of systems, creating design trade-offs between these qualities. The costs of execution and storage are important non-functional qualities, but as yet little is known about them for blockchain-based systems. How expensive is it to use blockchains compared to conventional execution and storage infrastructure? We investigate this question using business process execution as a lens. Specifically, we compare the cost for computation and storage of business process execution on blockchain vs. a popular cloud service. Besides monetary cost, blockchains like Ethereum limit the complexity of new blocks by capping costs through network-defined limits. For applications using such blockchains, the limit per block, thus, translates into an upper bound on throughput scalability. First, we implement and measure the cost of business process execution on blockchain and cloud services for a business process model from a large-scale industrial dataset and an example from literature. We observe two orders of magnitude difference in this cost. Second, we illustrate how cost models can be used to project the impact of different workload assumptions. Finally, we discuss throughput scalability limits as well as trade-offs between cost and other non-functional qualities in the design of blockchain-based systems.

A Survey on Homomorphic Encryption Schemes

Legacy encryption systems depend on sharing a key (public or private) among the peers involved in exchanging an encrypted message. However, this approach poses privacy concerns. The users or service providers with the key have exclusive rights on the data. Especially with popular cloud services, control over the privacy of the sensitive data is lost. Even when the keys are not shared, the encrypted material is shared with a third party that does not necessarily need to access the content. Moreover, untrusted servers, providers, and cloud operators can keep identifying elements of users long after users end the relationship with the services. Indeed, Homomorphic Encryption (HE), a special kind of encryption scheme, can address these concerns as it allows any third party to operate on the encrypted data without decrypting it in advance. Although this extremely useful feature of the HE scheme has been known for over 30 years, the first plausible and achievable Fully Homomorphic Encryption (FHE) scheme, which allows any computable function to perform on the encrypted data, was introduced by Craig Gentry in 2009. Even though this was a major achievement, different implementations so far demonstrated that FHE still needs to be improved significantly to be practical on every platform. Therefore, this survey focuses on HE and FHE schemes. First, we present the basics of HE and the details of the well-known Partially Homomorphic Encryption (PHE) and Somewhat Homomorphic Encryption (SWHE), which are important pillars for achieving FHE. Then, the main FHE families, which have become the base for the other follow-up FHE schemes, are presented. Furthermore, the implementations and recent improvements in Gentry-type FHE schemes are also surveyed. Finally, further research directions are discussed. This survey is intended to give a clear knowledge and foundation to researchers and practitioners interested in knowing, applying, and extending the state-of-the-art HE, PHE, SWHE, and FHE systems.

Performance analysis of multi-core VMs hosting cloud SaaS applications

Today's data centers are designed to scale up to respond to the offered workload in a rapid, efficient, and effective manner, and at the same time, they must satisfy the Service Level Agreement (SLA) requirements. This opens up many interesting and challenging research issues and opportunities. The Software-as-a-Service (SaaS) is the most popular cloud service model being used these days, in which multi-core VMs are allocated efficiently to meet the offered workload, and in a way to avoid any violations to the agreed SLA. This entails the need to model SaaS services to predict the performance and overall system cost, and to estimate the required number of VM resources and their respective multi-core capacity prior to the actual deployment. To this end, we present in this paper a queuing mathematical model to study and analyze the performance of multi-core VMs hosting cloud SaaS applications. Our analytical model estimates under any offered workload the number of required multi-core VM instances needed to satisfy the Quality of Service (QoS) parameters. Our mathematical model is validated using DES (Discrete Event Simulator) simulations. Results obtained from our analysis as well as simulation models show that the proposed model is powerful and able to correctly and effectively predict the system performance and cost, and also to determine the number of VMs cores needed for SaaS services in order to achieve QoS targets under different workload conditions.

ВИКОРИСТАННЯ ХМАРНИХ СЕРВІСІВ У РОЗВ'ЯЗАННІ ЛОГІЧНИХ ЗАДАЧ

The article provides an overview of the most popular cloud services, in particular those which have their complete office suites, the basic functional characteristics and highlights the advantages and disadvantages of cloud services in the educational process. It was made a comparative analysis of the spreadsheets that are in office suites such cloud services like Zoho Office Suite, Microsoft Office 365 and Google Docs. On the basis of the research and the findings it was suggested the best cloud services for use in the educational process. The possibility of using spreadsheets in the study of logic, from creating formulas that implement logical operations, the creation of means of automation of problem solving process was considered.

KBF: Towards Approximate and Bloom Filter based Key-Value Storage for Cloud Computing Systems

As one of the most popular cloud services, data storage has attracted great attention in recent research efforts. Key-value (k-v) stores have emerged as a popular option for storing and querying billions of key-value pairs. So far, existing methods have been deterministic. Providing such accuracy, however, comes at the cost of memory and CPU time. In contrast, we present an approximate k-v storage for cloud-based systems that is more compact than existing methods. The tradeoff is that it may, theoretically, return errors. Its design is based on the probabilistic data structure called “bloom filter”, where we extend the classical bloom filter to support key-value operations. We call the resulting design as the kBF (key-value bloom filter). We further develop a distributed version of the kBF (d-kBF) for the unique requirements of cloud computing platforms, where multiple servers cooperate to handle a large volume of queries in a load-balancing manner. Finally, we apply the kBF to a practical problem of implementing a state machine to demonstrate how the kBF can be used as a building block for more complicated software infrastructures.

An Algorithm for Finding the Minimum Cost of Storing and Regenerating Datasets in Multiple Clouds

The proliferation of cloud computing allows users to flexibly store, re-compute or transfer large generated datasets with multiple cloud service providers. However, due to the pay-as-you-go model, the total cost of using cloud services depends on the consumption of storage, computation and bandwidth resources which are three key factors for the cost of IaaS-based cloud resources. In order to reduce the total cost for data, given cloud service providers with different pricing models on their resources, users can flexibly choose a cloud service to store a generated dataset, or delete it and choose a cloud service to regenerate it whenever reused. However, finding the minimum cost is a complicated yet unsolved problem. In this paper, we propose a novel algorithm that can calculate the minimum cost for storing and regenerating datasets in clouds, i.e., whether datasets should be stored or deleted, and furthermore where to store or to regenerate whenever they are reused. This minimum cost also achieves the best trade-off among computation, storage and bandwidth costs in multiple clouds. Comprehensive analysis and rigid theorems guarantee the theoretical soundness of the paper, and general (random) simulations conducted with popular cloud service providers’ pricing models demonstrate the excellent performance of our approach.

A novel approach to manage cloud security SLA incidents

Cloud computing is increasingly playing an important role in the service provisioning domain given the economic and technological benefits it offers. The popularity of cloud services is increasing but so are their customers’ concerns about security assurance and transparency of the Cloud Service Providers (CSPs). This is especially relevant in the case of critical services that are progressively moving to the cloud. Examples include the integrated European air traffic control system or public administrations through the governmental clouds. Recent efforts aim to specify security in cloud by using security service level agreements (secSLAs). However, the paucity of approaches to actually control the fulfillment of secSLAs and to react in case of security breaches, often results in distrust in cloud services. In this paper, we present a solution to monitor and enforce the fulfillment of secSLAs. Our framework is able to (a) detect occurrences that lead to unfulfillment of commitments, and (b) also provide mitigation to the harmful events that may or do compromise the validity of secSLAs.