Cloud Solutions Research Articles

From Detection to Action: Implementing Deep Learning Inference in PLC Systems via Docker Services

This paper focuses on the implementation of recognition and detection algorithms for programmable logic controllers (PLCs) based on artificial intelligence (AI). AI methods based on deep neural networks (DNN) are characterized by a large number of hidden layers and neurons in hidden layers, which increases the computational complexity of computing the outputs of artificial neural networks (ANNs). Popular convolutional neural networks (CNN) are among such ResNet, AlexNet, GoogLeNet and others. A remote cloud solution is proposed in this paper to compute CNN outputs. The CNN implementation was tested on object recognition and detection applications. Training and testing of the CNN and YOLO detector was carried out in the Python environment.

Cloud Verse: Mapping the new frontiers of cloud computing

The endeavors to explore and map the dynamic terrain of cloud computing, designated as the CloudVerse. Through a meticulous examination of recent advancements and emerging patterns in cloud technologies, this study aims to furnish a comprehensive portrayal of the present state and future trajectories of cloud computing. Utilizing a blend of literature review and industry scrutiny, the paper identifies pivotal domains of innovation within the CloudVerse, encompassing hybrid cloud infrastructures, serverless computing models, edge computing paradigms, and AI-driven cloud solutions. Furthermore, it delves into the ramifications of these advancements across diverse sectors and deliberates on strategic imperatives for enterprises embracing cloud technologies. Ultimately, this inquiry strives to demarcate the contours and potentials inherent in the CloudVerse, proffering nuanced insights for navigating the intricacies of contemporary cloud computing landscapes.

ПРОТОКОЛ DDS КАК ЕДИНАЯ СРЕДА ПЕРЕДАЧИ ДАННЫХ В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ

For the effective development of agricultural complexes, the introduction of a variety of advanced technologies, including unmanned aerial vehicles, is especially important. In the distributed control systems used in various agricultural complexes and logging industries using unmanned aerial vehicles, the classical hardware and software architecture for creating such systems has been established. However, this approach has a number of significant drawbacks, in particular, the presence of a large number of different data bus standards at different levels of the platform architecture, which quite often significantly complicates the integration of individual parts of the system. The lack of a single standard within the software protocol for real-time data transmission leads to data fragmentation at all levels of the system as a whole. (Research Purpose) The research purpose is developing the concept of a hardware and software architecture for transmitting information data based on the Data Distribution Service protocol in real time as part of monitoring, managing and distributing tasks between unmanned aerial vehicles, as well as at all levels of a distributed agroforestry system using modern technologies and practices of the industrial Internet of Things. (Materials and methods) Used open sources of international communities in the field of automation and the industrial Internet of Things, as well as domestic and foreign scientific publications on this subject. The method of decomposition by automation levels was applied; the method of decomposition by functionality performed by individual hardware and software components of the system; the method of summarizing information from modern sources on the subject of research; formalization of hardware and software structures in the form of schematic diagrams. (Results and discussion) We have developed a concept for transmitting information data based on the Industrial Internet of Things Data Distribution Service protocol to ensure real-time data transmission. The proposed system makes it possible to implement unified information flows for monitoring and controlling unmanned aerial vehicles at all levels of a distributed agroforestry system. This helps simplify the integration of unmanned aerial systems into agroforestry systems of various orientation and complexity, eliminating difficulties in the interaction of various system components at all levels, including cloud solutions and other Industrial Internet of Things platforms. (Conclusions) As a result of the study, the problems of integrating the information flows of the agroforestry system and data transmission at its various levels were identified. It is proposed to use the Data Distribution Service data transfer protocol as a single standard at all levels of the system, which in the future will ensure compatibility and ease of integration of unmanned aerial vehicles of various manufacturers within a single system.

AWS Cloud Computing Solutions: Optimizing Implementation for Businesses

This study delves into the optimization strategies of Amazon Web Services (AWS) cloud computing solutions tailored specifically for businesses. It provides an in-depth exploration of the transformative impact that cloud computing has had on modern business operations, emphasizing the pivotal role played by AWS in delivering scalable, flexible, and cost-effective resources. With projections indicating the global public cloud services market's growth to $332.3 billion in 2021, it becomes evident that cloud solutions are increasingly relied upon, with AWS commanding a significant 32% market share. This paper highlights the importance of optimizing AWS solutions, considering its extensive range of services designed to meet diverse business needs. However, transitioning to cloud environments brings challenges related to data security, compliance, integration, and migration complexities, as evidenced by pertinent studies and literature reviews. This research synthesizes insights gleaned from various studies, emphasizing the adaptability and cost-effectiveness of AWS while stressing the critical role of robust security measures in its implementation across industries and geographic regions. Understanding prevalent business requisites and challenges in cloud adoption, including scalability, cost efficiency, reliability, availability, and compliance, is essential for organizations seeking to harness cloud technology effectively. Furthermore, this paper provides an overview of AWS's services encompassing computing, storage, databases, machine learning, and AI, showcasing how these empower businesses to streamline operations, foster innovation, and scale dynamically. It elucidates successful instances where AWS was strategically implemented in Netflix, Airbnb, Jollibee Group, and Capital One, demonstrating its impact on scalability, innovation, and service enhancement. The paper outlines anticipated trends in AWS and cloud computing, focusing on user-friendly tools, advancements in machine learning, infrastructure improvements, increased automation, and deeper integration of AI and advanced analytics. Ultimately, this research emphasizes business's need to optimize AWS solutions, navigate complexities, foster innovation, and achieve operational excellence in an increasingly competitive market.

From on-premise to cloud: Evolving IT infrastructure for the AI age

The transition from traditional on-premise IT infrastructure to cloud-based systems represents a fundamental shift necessary for the advancement and implementation of artificial intelligence (AI) technologies. This paper explores the critical role of cloud computing in supporting AI, emphasizing its benefits in terms of scalability, flexibility, and cost-efficiency. It examines the limitations of on-premise systems, the advantages of various cloud models (IaaS, PaaS, SaaS), and key considerations for successful cloud migration, such as data security, compliance, and cost analysis. Through a detailed case study of a financial institution's cloud migration for AI implementation, this study highlights the challenges, solutions, and lessons learned in the process. The case study provides practical insights into the phased approach to cloud migration, the use of hybrid cloud solutions as transitional strategies, and the importance of training and skill development for IT teams to ensure business continuity during the transition. Furthermore, the paper discusses future trends in cloud and AI integration, including the impact of emerging cloud technologies like server less and edge computing, and the pivotal role of 5G in enhancing cloud-based AI applications. It predicts the future landscape of cloud and AI integration, emphasizing the increasing adoption of hybrid and multi-cloud strategies, investment in data privacy and security, and the integration of AI with other emerging technologies such as IoT and block-chain. The paper concludes by underscoring the importance of cloud infrastructure in the AI age and calls for businesses to evaluate their cloud readiness to stay competitive in a rapidly evolving digital landscape. By embracing cloud-based solutions, businesses can unlock new opportunities for innovation, efficiency, and growth, positioning themselves at the forefront of the AI revolution.

From Scalar Clouds to Rotating Hairy Black Holes

First, we review the solutions of a complex-valued scalar field, termed scalar clouds, with and without electric charge, when coupled to a rotating Kerr–Newman (electrically charged) or Kerr (neutral) black hole (BH), respectively. To this aim, we determine the conditions and parameters that characterize the existence of solutions that represent bound states, with an energy-momentum tensor that respect the symmetries of the underlying spacetimes, even if the backreaction of the field is not taken into account at this stage. In particular, we show that in the extremal Kerr scenario the cloud solutions exist only when the mass of the BH satisfies certain bounds, which are obtained by analyzing an effective potential associated with the radial dependency of the scalar clouds that leads to a Schrödinger-like equation. Second, when the backreaction of the field in the spacetime is taken into account, we present a family of stationary, axisymmetric and asymptotically flat solutions of the Einstein–Klein–Gordon system that represent genuine rotating hairy black holes (RHBHs) and provide different values of some global quantities associated with them, such as the Komar mass and the Komar angular momentum. We also compute RHBH solutions with nodes in the radial part of the scalar field and also for a higher azimuthal number m.

Neural Network Multipath Routing in Software Defined Networks Based on Genetic Algorithm

Currently, a wide demand for the implementation and use of various cloud solutions is a modern trend and the driving force behind the development of network technologies. The growth of cloud application services delivered through data centers with varying network traffic needs demonstrates the limitations of traditional routing and load balancing methods. The combination of the advantages of software defined networks (SDN) technology and artificial intelligence (AI) methods ensures efficient management and operation of computer network resources. The paper proposes an approach to neural network multipath routing in SDN based on a genetic algorithm. The architecture and model of an artificial neural network has been developed to solve the problem of multipath routing in the SDN, which is able to predict the shortest paths based on the metrics of communication links. To optimize the hyperparameters of the neural network model, it is proposed to use a modified genetic algorithm. A visual software system SDNLoadBalancer has been developed and an experimental SDN topology has been designed, which makes it possible to study in detail the processes of neural network multipath routing in SDN based on the proposed approach. The obtained results show that the proposed neural network model has the ability to predict routes with high accuracy in real time, which makes it possible to implement various load balancing schemes in order to increase performance of SDN.

Optimizing Business Potential: A Framework for the Implementation of Cloud Computing by SMEs in the Bolgatanga Municipality, Ghana

Cloud computing has significantly impacted businesses across different scales, presenting advantages that can be harnessed by small and medium enterprises (SMEs) in Bolgatanga. However, the effective adoption of cloud services requires a well-defined strategy. SMEs in the Bolgatanga Municipality face challenges in implementing cloud computing due to limited knowledge of its applicability, a lack of expertise, and concerns about perceived high costs, among other factors. It was therefore necessary to develop a framework that can be utilized by SMEs in Bolgatanga to implement cloud solutions. The design science research methodology was employed where an extensive evaluation of existing cloud frameworks was performed. The findings suggest that although current cloud transition models have potential value, their complexity and lack of context applicability make them less suitable. The application of the design science research methodology paved way for the development of a practical framework for successful cloud computing implementation by SMEs in Bolgatanga, Ghana. The newly developed framework would enable SMEs to embrace the benefits of the emerging cloud computing era, reducing costs, and gaining a larger market share. Beyond the immediate benefits, leveraging cloud computing will promote collaboration, agile decision-making, and innovation. Cloud solutions provide scalability and accessibility, allowing SMEs to adapt quickly to market changes, improve customer experiences, and make significant progress in their industries. Implementing cloud computing strategically by SMES in Bolgatanga is therefore not just a technological upgrade but a crucial step towards unlocking substantial business advancements for SMEs.

МЕТОДИКА ФОРМУВАННЯ ПОНЯТЬ ІННОВАЦІЙНИХ SOFT SKILLS ЦИФРОВИХ ТЕХНОЛОГІЙ

The article is devoted to the problem of distinguishing the concepts of digital transformation, digitalization, digital technologies and soft skills of digital technologies, the structure and content of each of them is created. The concept of digital transformation is considered as the introduction of innovative technologies (artificial intelligence, cloud solutions, data analytics, the Internet of Things, etc.) into the life of society, which automatically changes the corporate culture and processes of using the power of these technologies. It’s not just a software or hardware update. it is a change in the way of thinking and new rules of doing business in a world where innovative technologies instantly determine the general rules of the game. Therefore, the concepts of digitization and digital technologies will be derived here. Having important conclusions about digital transformation, digitization and digital technologies, we came to the conclusion that digital components effectively contribute to the development of digital competences in the whole variety of digital soft skills. Digital technology is a big world where information is converted into bits, qubits, and trips and used for data processing, transmission, and storage. The structure of the concept of soft skills of digital technologies is clearly shown. It covers 12 concepts and 34 connections between them. They cover communication and collective platforms, time management, problem solving, critical thinking, adaptation, writing computer programs, programming languages, and others.

CIA-CVD: cloud based image analysis for COVID-19 vaccination distribution

Due to the huge impact of COVID-19, the world is currently facing a medical emergency and shortage of vaccine. Many countries do not have enough medical equipment and infrastructure to tackle this challenge. Due to the lack of a central administration to guide the countries to take the necessary precautions, they do not proactively identify the cases in advance. This has caused Covid-19 cases to be on the increase, with the number of cases increasing at a geometric progression. Rapid testing, RT-PCR testing, and a CT-Scan/X-Ray of the chest are the primary procedures in identifying the covid-19 disease. Proper immunization is delivered on a priority basis based on the instances discovered in order to preserve human lives. In this research paper, we suggest a technique for identifying covid-19 positive cases and determine the most affected locations of covid-19 cases for vaccine distribution in order to limit the disease's impact. To handle the aforementioned issues, we propose a cloud based image analysis approach for using a COVID-19 vaccination distribution (CIA-CVD) model. The model uses a deep learning, machine learning, digital image processing and cloud solution to deal with the increasing cases of COVID-19 and its priority wise distribution of the vaccination.Graphical

Determining job category using AWS machine learning cloud services

In this article, the focus is on the modern role of information technology in the labor market, with special emphasis on automation and optimization of processes through cloud solutions. The main theme is the creation of a system for the automatic categorization of job vacancies using Amazon Web Services (AWS). The authors describe the key advantages of implementing cloud technologies, such as scalability, cost savings, availability, and high productivity. Specific AWS services are then discussed, including ECS, DynamoDB, AWS Glue, Amazon SageMaker, and AWS Lambda, which can be applied for the implementation of this system. The article aims to show how AWS technologies can be used to improve efficiency.

A hardware and software complex for adaptive monitoring of a limited ecosystem with a cloud segment

In modern conditions, as Ukraine faces numerous challenges in the fields of ecology and security, the development of comprehensive monitoring methods for restricted ecosystems becomes increasingly relevant. The research resulted in the creation of a decomposed model for data movement within this closed system, featuring a modular structure. This is a crucial aspect for the rapid expansion of the existing system's functionality and the hot swapping of complex components. Upon reviewing the issue, it was determined that the methods of adaptive monitoring research for restricted ecosystems using special services on the potentially dangerous objects and objects of critical infrastructure were not sufficiently effective. The authors proposed, modeled, and developed a new hardware-software complex that enables the implementation of a set of tools specifically tailored for monitoring in areas of anthropogenic pollution. The optimal set of sensors for the sensor module was enhanced. A unique superposition of local and cloud solutions for data accumulation, analysis, processing, and visualization is recommended for further work in this and related fields. The integration of a new solution stack in the sub-gigahertz range, with the extension of the spectrum, distinguishes the project with resilience, while the Advanced Encryption Standard adaptation implements mid-attack protection. The expected effect of implementing the multisensory system lies in the early detection of emergency situation factors, forecasting, and decision-making regarding the elimination of the arising danger, as well as the prompt involvement of relevant units of the State Emergency Service of Ukraine and other government structures. The simple implementation mechanism of the system ensures scalability and the quick replacement of key elements.

Decentralized News-Retrieval Architecture Using Blockchain Technology

Trust is a critical element when it comes to news articles, and an important problem is how to ensure trust in the published information on news websites. First, this paper describes the inner workings of a proposed news-retrieval and aggregation architecture employed by a blockchain-based solution for fighting disinformation; this includes a comparison between existing information retrieval solutions. The decentralized nature of the solution is achieved by separating the crawling (i.e., extracting the web page links) from the scraping (i.e., extracting the article information) and having third-party actors extract the data. A majority-rule mechanism is used to determine the correctness of the information, and the blockchain network is used for traceability. Second, the steps needed to deploy the distributed components in a cloud environment seamlessly are discussed in detail, with a special focus on the open-source OpenStack cloud solution. Lastly, novel methods for achieving a truly decentralized architecture based on community input and blockchain technology are presented, thus ensuring maximum trust and transparency in the system. The results obtained by testing the proposed news-retrieval system are presented, and the optimizations that can be made are discussed based on the crawling and scraping test results.

An approach towards demand response optimization at the edge in smart energy systems using local clouds

The fourth and fifth industrial revolutions (Industry 4.0 and Industry 5.0) have driven significant advances in digitalization and integration of advanced technologies, emphasizing the need for sustainable solutions. Smart Energy Systems (SESs) have emerged as crucial tools for addressing climate change, integrating smart grids and smart homes/buildings to improve energy infrastructure. To achieve a robust and sustainable SES, stakeholders must collaborate efficiently through an energy management framework based on the Internet of Things (IoT). Demand Response (DR) is key to balancing energy demands and costs. This research proposes an edge-based automation cloud solution, utilizing Eclipse Arrowhead local clouds, which are based on Service-Oriented Architecture that promotes the integration of stakeholders. This novel solution guarantees secure, low-latency communication among various smart home and industrial IoT technologies. The study also introduces a theoretical framework that employs AI at the edge to create environment profiles for smart buildings, optimizing DR and ensuring human comfort. By focusing on room-level optimization, the research aims to improve the overall efficiency of SESs and foster sustainable energy practices.

ПРЕДПОСЫЛКИ И ПРОЦЕСС ЦИФРОВОЙ ТРАНСФОРМАЦИИ БАНКОВСКОГО СЕКТОРА РОССИЙСКОЙ ФЕДЕРАЦИИ

The article clarifi es the terms digitalization and digital transformation based on the experience of transforming the processes of credit institutions in Russia and research from foreign companies leading developments in the fi eld of information technology. By studying statistical data on the development of information technologies and the banking services provided, the prerequisites for digital transformation and the current state of the banking sector of the Russian Federation were determined. It was also determined that the introduction of fi nancial technologies represents fi nancial services and services aimed at introducing current tools for digitalization of the fi nancial sector into banking business processes, such as innovative technologies, big data, neural network algorithms, machine learning and artifi cial intelligence, cloud solutions and many other. It has been revealed that the development of financial technologies forms the basis for innovation-oriented development of the fi nancial sector, pursuing the goals of introducing unifi ed fi nancial ecosystems, transition to the latest formats for the provision of fi nancial services, and integration of promising start-up projects with innovative signifi cance and uniqueness. Based on the results of the study, prospects for the development of fi nancial technologies in the context of sanctions restrictions are formed, in particular, the continued development of trends in the popularization of the latest fi nancial technologies and the introduction of ecosystems, import substitution of technologies and overcoming the challenges of digital transformation of the banking sector, improvement of security issues, including through eff ective legal regulation from the regulator.

Artificial Intelligence in Healthcare: Risks and Opportunities

Today, one of the primary drivers of global economic growth is digital transformation. Artificial intelligence tools, cloud solutions and telemedicine technology seem to be critical components in the growth of different economic sectors, including healthcare. Like other developed countries, Russia believes that artificial intelligence can enhance access to high-quality and affordable medical care. The relevance of this topic is further supported by the President of Russia’s recent statements delivered at the opening events of health facilities around the country, where he emphasized the importance of incorporating artificial intelligence into all aspects of healthcare, including management, medicine, patient care, to ensure technological sovereignty. However, along with the obvious advantages, digital technologies particularly artificial intelligence, represent certain risks that are to be eliminated in order to achieve the core goal of improving the quality and accessibility of medical care.

Start thinking in graphs: using graphs to address critical attack paths in a Microsoft cloud tenant

AbstractThe challenge of securing IT environments has reached a new complexity level as a growing number of organisations adopt cloud solutions. This trend increases the possibility of overseen attack paths in an organisation’s IT infrastructure. This paper proposes a methodology for assessing the security of a Microsoft cloud tenant based on the relationships between different cloud entities through the use of graphs. This paper argues for using graph theory as an effective method to understand and uncover complex entity attack paths. To achieve this, we implemented a graph analytics platform using data from a Microsoft cloud test tenant. Methods based on graph theory proved to measurably reduce possible attack paths. Our research can support defenders who want to better understand the interrelationships of Microsoft cloud entities as well as identify and remediate possible attack paths.

Cloud Technology-Based Auditing and Accounting Services: General Outlook, Conditions, Issues and Review of Nigerian Accounting System

The purpose of this paper is to identifying the impact of Cloud Computing on the Elements of the Accounting and auditing Information System represented by: Establishment "Accounting Entity and internal controls.", Financial Operations, Documents, Accounting Books, Financial Reporting, Users, Procedures, Software, Physical Devices. Cloud technology-based auditing and accounting is one of the most promising and anticipated technologies in recent years. The technology is not a new concept for most of the sectors and with proper planning could increase operational efficiency. Integration of accounting and auditing informa Change in platform from in-house to cloud solution cannot change the role of the accounting information systems as a base for providing the financial information for decision-making to internal and external users, and therefore auditors will need to assess the risks associated with cloud accounting and they must gain knowledge of the new environment. Cloud technology-based auditing and accounting brought changes to auditing procedures but Security has been always raised as one of the most critical issues of cloud computing where resolving such an issue would result in constant growth in the use and popularity of the cloud. Security requirements represent a major issue that has to be met in order of easing some of these obstacles (Alam, 2020). As the focus is on information governance, IT management, network, data, contingency and encryption controls, auditors should have the appropriate knowledge of these areas and (as cloud technology-based auditing and accounting services depends on web services). Cloud accounting software enables its users a real time access to business finances, easy set up and easy use, access to information from anywhere, work with sales force, to synchronize instantly with bank, make tax returns precise and effortless. Cloud technology-based auditing and accounting offers a short implementation time and

Cloud-based solutions used by hungarian SMEs and analysis of its effects

The wide range of technological innovations took place in the post-millennium period and later became widely available have fundamentally reshaped the relationship between ICT infrastructure and business in the life of for-profit organizations. This is particularly true for the so-called primary (value-creating) processes. These technologies that have fundamentally transformed the way business organizations operate are collectively referred to as "Industry 4.0" technologies. A significant group of these technologies are the cloud-based solutions. By using these solutions, the users can get benefits from the ICT infrastructure through a third-party service. These services can be applications made available on a specific online interface (SaaS), or various platform elements (PaaS, for example: application servers, virtual servers, etc.) or infrastructure elements such as leased computing capacity (IaaS). By using cloud-based solutions, the customer can avoid the investment needed to run the ICT infrastructure and the additional problems rooted by the operation of ICT-infrastructure. A questionnaire survey was carried out in early 2019, in which 498 respondents voluntarily participated. The survey investigated the deployment level of ICT infrastructure among SMEs in Hungary, its information security consequences and how the management of the for-profit organizations evaluate the contribution of ICT infrastructure to the success of their business. The use of different cloud-based solutions was also measured in the mentioned questionnaire. The paper presents the research results of the prevalence of use of different cloud solutions with similar studies in the region. Furthermore, it examines whether cloud solutions have individually detectable beneficial effects on business operations, and whether synergies can be identified when multiple cloud applications are used together. Based on the qualitative results of the research and their interpretation, a broader analysis has been offered.

SYSTEM ANALYSIS OF THE USE OF CLOUD TECHNOLOGIES IN THE DIGITAL TRANSFORMATION OF UZBEKISTAN

Our article discusses the use of cloud technologies in the economy of Uzbekistan. And the role and importance of these technologies for improving economic processes is analyzed, in connection with which the leaders of the digital technology market continue to create and implement new cloud solutions to meet the needs of both the population and business structures.