Cloud Solutions Research Articles

An efficient Technique for Data Security using Improved Elliptic Curve Cryptosystem over Cloud Computing

Recent years have seen a rapid expansion of the cloud computing industry, which may be visualized as a distributed computing environment where cloud resources can be distributed shared. In comparison to traditional systems, there are thousands of computers operating in parallel, completing the specified task quickly. The parallel processing is made possible by the low cost of these virtualized hardware resources. In this paper, we discuss several cloud deployment options and how they differ from conventional computers in terms of security. Different methods that minimize the cloud and the limitations of current cryptographic techniques can be used to analyse this security. This research introduces ecliptic curve cryptography technique for various cloud-based applications and compares this technique with existing RSA algorithm-based applications to analyse the security in deployment models. The suggested elliptic curve based public key cryptography is shown to be superior to the current RSA algorithm based applications in this paper's experimental and theoretical results. Our experimental findings show that the suggested ECA approach outperforms the RSA algorithm. This aids in the use of security solutions for the various cloud computing deployment patterns that have been studied.

Applying Machine Learning in Cloud Service Price Prediction: The Case of Amazon IaaS

When exploring alternative cloud solution designs, it is important to also consider cost. Thus, having a comprehensive view of the cloud market and future price evolution allows well-informed decisions to choose between alternatives. Cloud providers offer various service types with different pricing policies. Currently, infrastructure-as-a-Service (IaaS) is considered the most mature cloud service, while reserved instances, where virtual machines are reserved for a fixed period of time, have the largest market share. In this work, we employ a machine-learning approach based on the CatBoost algorithm to explore a price-prediction model for the reserve instance market. The analysis is based on historical data provided by Amazon Web Services from 2016 to 2022. Early results demonstrate the machine-learning model’s ability to capture the underlying evolution patterns and predict future trends. Findings suggest that prediction accuracy is not improved by integrating data from older time periods.

Data Security in Foreign Computing: Cloud Solutions and their Impact on Cross-Border Data Integrity

Data Security in Foreign Computing: Cloud Solutions and their Impact on Cross-Border Data Integrity

A review on cloud security issues and solutions

Cloud computing provides computing resources, platforms, and applications as a service in a flexible, cost-effective, and efficient way. Cloud computing has integrated with industry and many other fields in recent years, which prompted researchers to look into new technologies. Cloud users have moved their applications, data and services to the Cloud storage due to the availability and scalability of Cloud services. Cloud services and applications are provided through the Internet-based on a pay-per-use model. Plenty of security issues are created due to the migration from local to remote computing for both Cloud users and providers. This paper discusses an overview of Cloud computing, as well as a study of security issues at various levels of Cloud computing. The article also provides a complete review of security issues with their existing solutions for a better understanding of specific open research issues.

SwarmAd: A decentralised content management system

AbstractOnline presence is becoming an important part of everyday's life and online communities may represent a significant source of engagement for the elderlies. Nevertheless, many may struggle to be online due to a lack of expertise, and a decentralised architecture may provide a solution by removing intermediaries, such as a webmaster, while not requiring expensive cloud solutions. However, issues concerning accessibility, security, and user experience have to be tackled. The paper focuses mainly on three issues: providing a human‐readable domain, moderating content, and creating a reward system based on user reputation. An architecture is proposed based on Ethereum and Swarm. Smart contracts provide an automated set of rules to handle enterprise registration, content creation, and decision‐making process, while Swarm serves both as distributed storage and the web host. Besides, in combination with Ethereum Name Service, Swarm provides a secure, distributed, and human‐readable point of access to the web interface. The paper also describes an innovative two‐token system where one token is meant to be a trustworthy reputation metre and the other is a spendable coin to get rewards. The final result is a fully decentralised, authenticated and moderated platform where users can aggregate and share their content presentations on the Internet.

Leveraging SMEs technologies adoption in the Covid-19 pandemic: a case study on Twitter-based user-generated content

The COVID-19 pandemic has caused many entrepreneurs and small and medium enterprises (SMEs) to adapt their business models and business strategies to the consequences caused by the pandemic. In order to identify the main innovations and technologies adopted by SMEs in the pandemic, in the present study, we used a database of 56,941 tweets related to the coronavirus to identify those that contained the hashtag #SMEs. The final sample was analyzed using several data-mining techniques such as sentiment analysis, topic modeling and textual analysis. The theoretical perspectives adopted in the present study were Computer-Aided Text Analysis, User-Generated Content and Natural Language Processing. The results of our analysis helped us to identify 15 topics (7 positive: Free support against Covid-19, Webinars tools, Time Optimizer and efficiency, Business solutions tools, Advisors tools, Software for process support and Back-up tools; 4 negative: Government support, Payment systems, Cybersecurity problems and Customers solutions in Cloud, and and 4 neutral: Social media and e-commerce, Specialized startups software, CRMs and Finance and Big data analysis tools). The results of the present study suggest that SMEs have used a variety of digital tools and strategies to adapt to the changing market conditions brought on by the pandemic, and have been proactive in adopting new technologies to continue to operate and reach customers in a connected era. Future research should be directed towards understanding the long-term effects of these technologies and strategies on entrepreneurial growth and value creation, as well as the sustainability of SMEs in the new era based on data-driven decisions.

The Benefits and Challenges of Customization within SaaS Cloud Solutions

The Benefits and Challenges of Customization within SaaS Cloud Solutions

Analysis the Success of Using a Project Management Tool in Managing Projects

Using Jira is considered an application with an easy-to-understand interface and customization features for each project. However, in the daily use of Jira, there are still obstacles faced by employees, namely, project status information is still inaccurate, lack of employee knowledge on how to configure Jira so that it takes a long time to meet the needs of each project and features that are still found do not function optimally. Hence, it hinders the process of using Jira in project management. This study aims to determine the success factors of using Jira in managing projects in the Cloud solution provider industry. This study uses a quantitative method to assess the constraints and factors that influence the success of project management tools by distributing questionnaires to employees. The findings in this study are that the socio-cultural variables and technical knowledge do not significantly affect the success of project management tools. However, the variables of personal characteristics and team capabilities are proven to significantly influence the success of project management tools, and the variables of training and learning are proven to have a moderating effect on the variable of team capabilities on the success of project management tools. Personal characteristics and social culture variables have a significant influence on team capability variables.

Automated methods for indoor point cloud preprocessing: Coordinate frame reorientation and building exterior removal

Raw indoor datasets acquired from laser scanning may be tilted and contain outliers, which negatively influence the accuracy of subsequent tasks. Therefore, an automatic framework with three steps is provided to preprocess indoor point cloud. First, a hybrid segmentation method is proposed to extract planar primitives from noisy points. Then, a nonlinear optimization is designed to discover the dominant orientations of the building with topological constraints. Finally, the outdoor points are removed through a novel graph-cut formulation. The experiments on six various buildings indicates that our methods successfully reorient the point cloud and preserve the indoor points. In comparison with other methods, we achieve superior performance on visual inspection and evaluation metrics. Besides, our work only relies on the geometric position and is not limited by Manhattan-World assumption. We present a reliable solution for indoor point cloud preprocessing that have potential for indoor modelling, floorplan generation, and objects detection.

The Role of Cloud Computing in Modernizing Healthcare IT Infrastructure

The modernization of healthcare IT infrastructure has been aided by cloud computing, which has revolutionized the methods for storing, processing, and accessing medical data. In order to better understand how cloud computing is contributing to the advancement of healthcare technology, this study will concentrate on how it affects the handling of data, seamless integration, and system efficiency in general. Significant benefits come from the use of cloud computing in healthcare, including improved scalability and flexibility in managing enormous volumes of patient data. By leveraging storage via cloud solutions, health care providers can seamlessly multiply the information they store storage capabilities, welcoming an increasing number of medical data and diagnostic imaging. Healthcare practitioners may now access data more easily thanks to its scalability, which encourages prompt and well-informed decision-making. Furthermore, cloud computing promotes smooth communication and data interchange by facilitating interoperability across heterogeneous healthcare systems. The integration of electronic medical records, or EHRs, and other health information systems is made possible by standardized interfaces and protocols, which foster a cohesive healthcare ecosystem. This interoperability promotes a more comprehensive approach to the treatment of patients in addition to improving provider collaboration. The study also addresses the consequences of cloud computing for maintaining data security and regulatory compliance. To protect sensitive patient data, cloud service providers frequently have strong security measures in place, like encryption and access controls. Furthermore, cloud infrastructure's flexibility enables healthcare companies to easily adjust to changing regulatory requirements. A critical first step toward modernization is the incorporation of cloud computing into healthcare IT infrastructure. Cloud-based solutions' scalability, interoperability, and security not only solves immediate problems but also sets the healthcare sector up for future advancements in healthcare and information storage.

ХМАРНІ РІШЕННЯ РЕАЛІЗАЦІЇ ГІБРИДНОЇ IT-ІНФРАСТРУКТУРИ ІНФОРМАЦІЙНО-ОСВІТНЬОГО СЕРЕДОВИЩА ВИЩОГО ВІЙСЬКОВОГО НАВЧАЛЬНОГО ЗАКЛАДУ

According to the cloud-based project, the information and education environment (IE) of a higher military educational institution is being modernized. Hybrid IT infrastructure and cloud solutions for its implementation are analyzed. As a result, a comprehensive model of dialogically close service solutions is presented as a prototype of an open, coordinated and standardized cloud system. The hierarchical two-level structure of the complex model is represented by: at the lower (physical) level, hardware for providing cloud services; at the upper (abstract) level, physically deployed software. The article presents a combined scheme of corporate IT infrastructure maintenance with priority given to the IaaS services segment, the classic scenario of hybrid IT infrastructure deployment, and a ready-made management software solution. These requirements have been transformed into a cloud-based hybrid system architecture that combines the external infrastructure of service providers with the internal local infrastructure of a military educational institution by integrating corporate resources and services into the information and educational environment. The latter are represented by ready-made solutions from Microsoft Azure, Office 365, Imagine Academy, Virtual Academy, and Google Workspace, which Microsoft and Google provide to educational institutions free of charge. The basic version of the freely distributed cloud platform Apache CloudStack v.4 was chosen as a tool for managing the resources of the hybrid IT infrastructure. In this context, the selection criteria and the overall topological ordering of the cloud platform are defined. The organizational emphasis of the platform implementation as a three-level hierarchical investment of structural elements is set. We propose a technical structure of the implementation consisting of two computers, one of which performs the functions of the CloudStack MS Management Server and the Primary Storage, and the other is responsible for the hypervisor and contains the Secondary Storage. Keywords: information and educational environment, hybrid IT infrastructure, virtualization, service solutions, cloud platform, virtual machine, deployment model.

IOT Based Smart Chair to Help with Back Pain

Abstract: This Poor sitting posture is a common cause of low back pain, as it places excessive pressure on muscles and discs. To address this issue, smart office chairs have been developed using IoT, wireless communication, sensing, and intelligent control technologies. This paper proposes and implements a system for detecting incorrect sitting positions using a smart chair equipped with two tactile pressure sensor mats, vibration actuators, NodeMCU , a data acquisition module, and a cloud server. The system notifies users of incorrect sitting positions through visual and vibration feedback, which is received through a mobile application. Simple rules were defined to process sensor data to recognize wrong sitting postures, and the data collected from smart chairs were stored in a MongoDB database using a private cloud solution from QNAP. The Node-RED application was proposed for the entire logic implementation.

A scalable offline AI-based solution to assist the diseases and plague detection in agriculture

ABSTRACT Early detection of diseases and pests is a key factor in eradicating or minimising the damage that these may cause. In this work, a comprehensive solution is presented that is based on the composition of existing cloud solutions and mobile tools to detect in-situ issues. The platform presented was used for the detection of powdery mildew and Cladosporium diseases in tomatoes. The results of using the approach to carry out this task were more than satisfactory since it managed to correctly detect the symptoms, having mAP of 0.41 in at least some of these symptoms. We analysed the performance of our dataset, on the one hand, and the combination of PlantDoc dataset, on the other hand. This shows that the platform can be used in the agriculture sector, as an additional tool for detecting diseases and pests in order to combat the problem and reduce its consequences.

IoT Sensor Challenges for Geothermal Energy Installations Monitoring: A Survey

Geothermal energy installations are becoming increasingly common in new city developments and renovations. With a broad range of technological applications and improvements in this field, the demand for suitable monitoring technologies and control processes for geothermal energy installations is also growing. This article identifies opportunities for the future development and deployment of IoT sensors applied to geothermal energy installations. The first part of the survey describes the technologies and applications of various sensor types. Sensors that monitor temperature, flow rate and other mechanical parameters are presented with a technological background and their potential applications. The second part of the article surveys Internet-of-Things (IoT), communication technology and cloud solutions applicable to geothermal energy monitoring, with a focus on IoT node designs, data transmission technologies and cloud services. Energy harvesting technologies and edge computing methods are also reviewed. The survey concludes with a discussion of research challenges and an outline of new areas of application for monitoring geothermal installations and innovating technologies to produce IoT sensor solutions.

A Prototype for Automated Delimitation of Work Cycles from Machine Sensor Data in Cable Yarding Operations

The demand for increased efficiency in timber harvesting has traditionally been met by continuous technical improvements in machines and an increase in mechanisation. The use of active and passive sensors on machines enables improvements in aspects such as operational efficiency, fuel consumption and worker safety. Timber harvesting machine manufacturers have used these technologies to improve the maintenance and control of their machines, to select and optimise harvesting techniques and fuel consumption. To a more limited extent, it has also been used to evaluate the time taken to complete tasks. The systematic use of machine sensor data, in a central database or cloud solution is a more recent trend.Machine data is recorded over long periods of time and at high resolution. This data therefore has considerable potential for scientific investigations. For mechanised timber harvesting operations, this could include a better understanding of the interaction between productivity and operational parameters, which first of all requires an efficient determination of cycle time.This study was the first to automatically delimitate tower yarder cycle times from machine sensor data. In addition to machine sensor data, cycle times were collected through a traditional manual time and motion study, and cycle times from both studies were compared to a reference cycle time determined from video footage of the yarder in operation.Based on three days of detailed time study, the total cycle time in the classic manual time (–1.3%) and in the machine sensor data (–1.2%) was only slightly shorter than in the reference study, and the average cycle time did not differ significantly (classic manual time study: –0.08±0.94 min, p=0.997; machine sensor data study: –0.08±0.26 min, p=0.997). However, the accuracy of the machine sensor approach (RMSE=0.92) was more than three times higher than that of the classic manual time study (RMSE=0.27).With the integration of sensors on forestry machines now being commonplace, this study shows that machine sensor data can be reliably interpreted for time study purposes such as machine or system optimisation. This eliminates the need for manual time study, which can be both cumbersome and dependent on the experience of the observer, and allows long term data sets to be obtained and analysed with comparatively little effort. However, a truly automated time study needs to be supplemented with automated determination of and linkage to other operational parameters, such as yarding and lateral yarding distance or load volume.

Integration of Machine Learning Solutions in the Building Automation System

This publication presents a system for integrating machine learning and artificial intelligence solutions with building automation systems. The platform is based on cloud solutions and can integrate with one of the most popular virtual building management solutions, HomeAssistant. The System uses communication based on the Message Queue Telemetry Transport (MQTT) protocol. The example machine learning function described in this publication detects anomalies in the electricity waveforms and raises the alarm. This information determines power quality and detects system faults or unusual power consumption. Recently, increasing electricity prices on global markets have meant that buildings must significantly reduce consumption. Therefore, a fundamental element of energy consumption diagnostics requires detecting unusual forms of energy consumption to optimise the use of individual devices in home and office installations.

Embedding The Fourth Industrial Revolution (4IR) in South African Municipalities: Challenges and Prospects

In South Africa, the current technology has brought multitudes of changes and transformations to the public sector and service delivery. The current state of technology allows municipalities to carry out their duties using ICT platforms successfully. E-participation, e-services, citizen portals, digital city services and goods, broadband fibre rollouts, CCTV networks, data center infrastructure, and private cloud solutions are just a few of these endeavours. The lack of integration of the smart city plan into the IDP, insufficient internal ability to support and sustain projects, and other issues may prohibit most municipalities from effectively adopting 4IR programs. limited support from a broader range of stakeholders, such as workers, communities, labourers, and businesses Among municipal departments, there is a lack of linked and coordinated thinking and activities. This study aims to assess how well the 4IR has worked to improve municipal service delivery. It is concluded that towns may be able to fully integrate modern technologies with the incorporation of 4IR technology into municipal IDP. In order to do this, a number of strategies are suggested, and a theoretical framework for the phenomena is investigated, with the goal of addressing the issues that prevent the proper application of 4IR technologies in South African Municipalities.

Adoption Strategy for Cloud Computing in Kenyan Research Institutions

Cloud computing has transformed the aspect of distributed computing from many other prevailing methods by offering more unlimited benefits, like cutting down computing costs and allowing more capacity and agility. It is viewed as a game-changer in how information technology is provided since it allows computer resources like storage, processing capacity, network infrastructure, and applications to be offered as a service via the Internet. In business, it seems to have become strategic, with the potential for use in crucial parts of an organization's IT infrastructure, as it offers a potential alternative to traditional Enterprise Resource Planning (ERP) systems. Most Kenyan research institutes' systems experienced certain flaws and recognized incidents of system rigidity, which prevented these institutions from efficiently meeting their mandate, especially when they desired to access services from home via the Internet. The Research design that was utilized in the study was a survey research design. The study employed a systematic review approach that examined the current literature on cloud computing adoption strategy. The systematic literature review revealed that existing research was dominated by issues of the characteristics/peculiarities and IT environments of research institutions in Kenya and if they were amenable to cloud solutions, the current cloud computing technologies, adoption approaches and drivers fostering cloud computing and the adoption strategy that met the requirements for cloud computing for Kenyan research institutions. The present research was reviewed for knowledge gap identification purposes and future research opportunities. The researcher developed an adoption strategy favorable to research Institutions that was flexible to the provision of cloud computing resources, enhanced greater cloud computing efficiency, reduced capital expenditure in hardware and software and increased the performance of the research Institution's operations, provided the efficiency of data and information and supported the effectiveness of the management activities since the cloud strategies discussed did not promote cooperation, agility, scalability and flexibility and saving costs by using calculating resources efficiently and optimally. This study employed a purposive sampling approach that picked a sample size of twenty respondents from the KMFRI and related organizations. The analytical review of specifically identified studies exposed the kind of challenges that existed and gave an indication that cloud computing was applicable for Kenyan Research Institutions because of the organization size, possession of required skills to make use of cloud-based services, Government regulations, industry regulations and internal policies necessitated the move to cloud computing strategy. The cloud service providers have adequate capacity to run the services and are ready with the services they provide. Researchers noted that all the research Institutions have dedicated ICT personnel and ICT Policies. Efficient service delivery means there is easy access to any research information from the cloud at any time and anywhere. Using Factor Analysis, variable weights for various study constructs (Technological, Internal and External Contexts) were used to develop the adoption strategy for cloud computing (ASCC). The recommendations of the study from the developed strategy showed that the network infrastructure should be more developed so that the Kenyan Research Institutions can be connected to high-speed Internet to allow for sharing of information, which will ensure efficient service delivery using cloud computing services. The study also recommended that Kenyan Research Institutes train their customers and suppliers on using cloud computing services for efficient service delivery and the adoption strategy for cloud computing (ASCC) to achieve efficiency in service delivery. Areas for further related studies can be conducted to determine the long-term impact of the developed adoption strategy for adopting cloud computing in Kenyan research Institutions. Also, further studies could carry out to determine ways of improving the developed adoption strategy for the adoption of cloud computing in Kenyan Research.

A use-case-driven approach for demonstrating the added value of digitalisation in wind energy

Digitalisation is one of the key drivers for reducing the costs and risks of wind energy. When considering whether to embark on a digitalisation initiative, two key questions arise. The first is what business or operational opportunities might feasibly be addressed and the second is which of the many potential aspects of digitalisation are relevant to those opportunities. In this work, we show how these questions can be answered with a use-case-driven approach, based around a survey aiming to collect and collate the main ”pain points” (or everyday challenges) of people in the wind energy sector. Although the relatively low number of participants of the survey (46) means that the results should only be used indicatively, it is still possible to make some general recommendations for priorities for digitalisation efforts in the wind energy sector. Firstly, digitalisation efforts should focus both on supporting people carrying out cross-lifecycle tasks, in particular sharing data, managing data, undertaking general data analyses and accessing data. Tools to do this should deal with varying data formats and naming conventions, make metadata more accessible, define data and metadata standards, make more data publicly available and improve the quality of data. Secondly, efforts should also focus on supporting people in the wind farm operational phase, in particular with failure detection, fault diagnosis, failure rate modelling and predictive maintenance. Solutions to do this should focus on accessible and validated tools for fault detection, cloud or other data pipeline solutions for SCADA data and tools for exhaustive data documentation. Finally, digitalisation efforts should focus on better communicating and helping people become aware of existing solutions and tools, as well as on helping people to exert a stronger influence on possible solutions.

High precision numerical sequences of rotating hairy black holes

We analyze numerically the existence of regular stationary rotating hairy black holes within the framework of general relativity, which are the result of solving the Einstein-Klein-Gordon system for a complex-valued scalar field under suitable boundary (regularity and asymptotically flat) conditions. To that aim we solve the corresponding system of elliptic partial differential equations using spectral methods which are specially suited for such a numerical task. In order to obtain such system of equations we employ a parametrization for the metric that corresponds to quasi-isotropic coordinates (QIC) that have been used in the past for analyzing different kinds of stationary rotating relativistic systems. Our findings are in agreement with those reported originally by Herdeiro and Radu. The method is submitted to several analytic and numerical tests, which include the recovery of the Kerr solution in QIC and the cloud solutions in the Kerr background. We report different global quantities that allow us to determine the contribution of the boson hair to the spacetime, as well as relevant quantities at the horizon, like the surface gravity. The latter indicates to what extent the hairy solutions approach the extremal limit, noting that for this kind of solutions the ratio of the angular momentum per squared mass ${J}_{\ensuremath{\infty}}/{M}_{\mathrm{ADM}}^{2}$ can be larger than unity due to the contribution of the scalar hair, a situation which differs from the Kerr metric where this parameter is bounded according to $0\ensuremath{\le}|J/{M}^{2}|\ensuremath{\le}1$, with the upper bound corresponding to the extremal case.