Cloud Computing Research Research Articles

Challenges and Solutions for Sustainable ICT: The Role of File Storage

Digitalization has been increasingly recognized for its role in addressing numerous societal and environmental challenges. However, the rapid surge in data production and the widespread adoption of cloud computing has resulted in an explosion of redundant, obsolete, and trivial (ROT) data within organizations’ data estates. This issue adversely affects energy consumption and carbon footprint, leading to inefficiencies and a higher environmental impact. Thus, this opinion paper aims to discuss the challenges and potential solutions related to the environmental impact of file storage on the cloud, aiming to address the research gap in “digital sustainability” and the Green IT literature. The key findings reveal that technological issues dominate cloud computing and sustainability research. Key challenges in achieving sustainable practices include the widespread lack of awareness about the environmental impacts of digital activities, the complexity of implementing accurate carbon accounting systems compliant with existing regulatory frameworks, and the role of public–private partnerships in developing novel solutions in emerging areas such as 6G technology.

Mapping the Evolving Landscape of Cloud Computing Research: A Bibliometric Analysis

This research paper presents an in-depth bibliometric analysis of cloud computing literature, aiming to uncover underlying patterns, assess citation levels, and identify key trends shaping this rapidly evolving field. The study employs robust bibliometric techniques, analyzing data collected from reputable academic databases, including Scopus. The methodology involves comprehensive data acquisition, preprocessing, analysis, and interpretation, using advanced tools like VOSviewer and Biblioshiny for visualization and statistical analysis.Our findings reveal significant growth in cloud computing research from 2019 to 2023, with a fluctuating yet ascending trajectory of scholarly output. Key contributors include China and India, underscoring their roles in advancing cloud computing research. The analysis of keyword frequency highlights 'cloud', 'data', 'computing', 'security', and 'block chain' as dominant themes, indicating a strong emphasis on data integrity, security, and emerging technologies in cloud computing.Sentiment analysis of research abstracts reveals a predominantly positive yet cautiously optimistic tone, reflecting the field's optimistic outlook towards advancements and potential applications, balanced by an awareness of inherent challenges. The study also delves into the impact of authors and organizations, identifying influential contributors and collaborative networks within the academic community.In conclusion, this paper provide a comprehensive overview of the cloud computing research landscape, offering valuable insights for researchers, policymakers, and industry leaders. It underscores the significance of cloud computing in modern society and highlights the need for continued exploration and innovation in this critical technology domain.

Research in Cloud Computing

Research in Cloud Computing

Application of computer image technology in 3D painting based on cloud computing

Virtual painting technology is a new technical means of modern art creation. 3D painting is a branch of virtual reality art. It uses computers or other intelligent computing devices to simulate the virtual 3D space environment, so that art creators can immerse themselves in painting creation. The difference between 3D painting and traditional painting is that it is a painting space from two-dimensional to three-dimensional. It is a painting creation process of double immersion of human brain and limbs. We believe that the artistic exploration of 3D painting is helpful to the improvement of painting artistic creation ideas and the expansion of skills. It is an embodiment of enriching the media and visualization of painting. Due to the complexity of 3D painting, this paper creates a cloud platform based on the high-speed and large storage characteristics of cloud computing, which will provide more efficient and convenient experience for 3D painting users. The key to the development of the cloud platform is to build an NX digital modeling and display platform based on cloud computing. Through the compression, serialization and network transmission of the three-dimensional image technology at the NX end, the three-dimensional model is finally displayed in the browser interface, and the basic functions of interacting with the model are provided for users. Cloud computing technology is used to arrange the computing work of 3D model compression into subsequent computing, which greatly reduces the redundancy of users' work. Through the research of cloud computing, this paper applies it to computer image technology, which makes the application of 3D painting flourish.

Mobile Cloud Computing Research: Issues and Challenges

Mobile Cloud Computing Research: Issues and Challenges

Genetic Algorithm-Based Optimal Resource Trust Line Prediction in Cloud Computing

A cloud computing signifies a novel computing paradigm that endorses reactive delivery of resources and services. A distinctive cloud service of such data center deploys over many computing nodes requesting services from the data centers. The organization of resources and trustworthiness of client is a hot topic of research in cloud computing. One of the major threats in cloud computing is unauthorized access of hardware and their resources. To conquer the issue, this novel work proposes an Optimal Resource Trust line prediction using Genetic Algorithm (GAORTL). The main aim of the work is to find the allocated optimal resource utilization of clients through an evolutionary algorithm. Implementation is evaluated to prove the benefit of the algorithm. Subsequently, we perform a comprehensive investigation that the proposed GAORTL delivers a better prediction of trustworthiness in variety of client sizes for a big scale batch of occurrences.

Descriptive Literature Review and Classification of Community Cloud Computing Research

Cloud computing has been devoted to the development of recent advanced technology, aiding in improving a government’s functioning and the services it offers to its people and organizations. It has achieved widespread popularity due to the rising number of benefits, including scalability, versatility, reliability, safety, confidentiality, pay-per-use, and dynamicity for the distribution of IT services. This paper explores a descriptive literature review and aims to classify the scattered communities involved in cloud computing research in information technology. This involves 51 referred published articles between 2010 and 2020 relating to the inception of community cloud computing by various organizations. Based on a systematic structured of reviewed literature and grounded theory approach, articles are categorized with respect to the eleven key influencing variables: cost, security, performance, QoS, trust, accuracy, ease of use, usefulness, architecture, framework, and model. Following that, those variables are comprehended into final one in order to envisage the community cloud computing adoption factors and concepts. This will consent for a strong examination of the community cloud computing phenomenon. The study is a novel attempt to demonstrate the differences in key factors for cloud computing in varying community settings and their causal relationships among the considered variables. The findings from the long-term systematic review contribute by assisting a collection of determinants for the penetration of community clouds services and potential adopters. It could serve as a basis for future directions and the development of theories in the exploring the community cloud computing in the field of information systems. This study contributes to identify various existing research gaps by providing holistic insights and future exploratory approaches that are anticipated to result in a robust unified structure for the adoption of community cloud computing services in the higher education institution (HEIs).

Green Cloud Computing (GCC), Applications, Challenges and Future Research Directions

Green Cloud Computing (GCC), Applications, Challenges and Future Research Directions

Cloud computing rising in the field of big data and artificial intelligence

Cloud Computing is a strong, large-scale and complex Computing technology. It lessens the need to maintain an expensive, specialized computer hardware area, as well as expensive software and software. Cloud computing has shown a significant increase in data quality or the production of large amounts of data. Big data processing is a difficult and time-consuming operation that necessitates the use of a large computer system in order to ensure performance. Knowledge creation and analysis are two intertwined activities and this paper investigates the rise of Big Data and Artificial Intelligence (AI) in Cloud Computing research. As data storage and mining methods advance, the preservation of expanding data quantities is characterized by a change in the core of structured results. This shift is reflected in the evolution of structured results. However, one major barrier is that this rate of growth surpasses the ability of data gathering systems and cloud infrastructure platforms to be upgraded. Workloads are really heavy and it is possible that certain cloud computing disputes will be created, which will include the description, characteristics, and categorization of huge data. In addition, analysis problems based on data integrity, heterogeneity and protection.

Research and Application of Cloud Computing and Big Data Technology

The combined application of new network technologies with the traditional Internet and industry has enabled new businesses such as the Internet of Things and cloud computing to be gradually derived. To realize the construction of a modern society in China, great attention should be paid to the application of new network technologies such as cloud computing in actual work. Now through data integration and correlation analysis, the accuracy and innovation of information are further realized, and the overall work efficiency and work quality are improved. This paper systematically analyzes the network big data technology and applications of cloud computing and Internet of Things, and conducts research from data collection, data integration, data processing, and data governance. Its main purpose is to make the value and function of these new network technologies fully utilized

Research on the Development of Innovation Path of Ideological and Political Education in Colleges and Universities Based on Cloud Computing and K-Means Clustering Algorithm Model

As a distributed computing technology, cloud computing has the characteristics of fast processing speed, large-capacity data processing, and high overall efficiency. With the continuous development of communication technology today, cloud computing technology has begun to be applied in various industries and has promoted the development and progress of the industry. As an important part of college education, ideological and political education in colleges and universities is also constantly developing. The integration of cloud computing and ideological and political education is the main trend in the future. At present, the application research of cloud computing and wireless communication technology in the ideological and political education of colleges and universities has obtained some results, but there are still some problems. Therefore, the research on innovative methods of ideological and political education is extremely important. At present, under the attention of all walks of life, scholars have strengthened the research on new paths of ideological and political education in colleges and universities, and they are also constantly experimenting with innovative methods. In this context, this paper studies the current situation of ideological and political education in colleges and universities through questionnaire surveys and analyzes the innovative mode of ideological and political education in colleges and universities in the context of cloud computing through the K-means clustering algorithm model.

Cloud computing and human resource management: systematic literature review and future research agenda

PurposeThis study aims to provide an overview of what characterizes the current state of research in the field of cloud computing use in human resource management (HRM) with the identification, analysis and classification of the existing literature and lines of research addressed and to provide guidance for future research.Design/methodology/approachThe systematic literature review (SLR) technique has been used to identify, select, analyze and evaluate the existing publications on cloud computing and HRM. A total of 35 papers published up to December 2020 have been obtained from the Web of Science (WoS) scientific database. The research design has allowed us to determine what characterizes the current state of research on the use of cloud computing in HRM and obtain a novel classification of the literature that identifies four lines of research and the contributions in each line and has allowed us to define the future research agenda.FindingsThe four groups into which the papers on the cloud computing-HRM relationship have been classified are: (1) studies focused on the development of cloud platforms for HRM that highlight technical aspects, (2) papers that focus on the concept of human resource elasticity, (3) papers on the adoption and/or implantation of cloud platforms for HRM and (4) studies that highlight the effects or implications of cloud platforms for HRM. This paper proposes some new opportunities for future research and presents some helpful implications from the theoretical and management perspectives.Research limitations/implicationsThis study uses only scientific articles in the WoS database with a Journal Citation Report (JCR) or SCImago Journal Rank (SJR) impact.Originality/valueThis paper provides an overview of the knowledge on cloud computing and HRM research and offers recommendations for future research.

Exploitative or explorative innovation? An event study of cloud computing business value

Firms may invest in cloud computing for exploitative or explorative innovation. Exploitative innovation oriented cloud computing investments impact the firms' core business limitedly while the investments for explorative innovation bring the firms both more opportunities and risks such as complex integration with multiple participants. Different enterprises should invest in cloud computing for different orientations according to their situations so as to fully realize the business value. This study examines how the business value of cloud computing is contingent on the investment orientations and the contextual factors of firm characteristics. Taking 183 Chinese listed companies adopted cloud computing as the research sample, we conduct event study methodology to investigate the business value of cloud computing regarding the focal firms' objectives and characteristics including organizational inertia, innovation capability and industry types. The results show that the business value of cloud investment for explorative innovation is more positive than that for exploitative innovation especially for the innovative firms with weak organizational inertia in non-service industries. Meanwhile, achievement of cloud computing business value is complementary to overcoming organizational inertia and promoting innovation capability. This study extends the boundary of business value research of cloud computing and provides references for cloud investment decision making.

RETRACTED ARTICLE: Simulation of enterprise accounting information system based on improved neural network and cloud computing platform

With the development of science and technology and the application of big data technology, a new computing model based on the Internet has gradually been applied to all levels of society. This kind of computing technology relying on big data is also known as cloud computing, which can continuously integrate the collected big data and process the data by categories, so that the data can be used most efficiently. This will improve the user experience and enable users to enjoy the service of big data whenever and wherever. At the same time, advanced technology can also be combined with new service mode, which has become an important turning point in the development of modern service industry. For most enterprises, informatization is an inevitable development path. In order to improve the efficiency of enterprise accounting, we hope that the research of cloud computing can improve the efficiency of enterprise accounting and improve the development of enterprise information system.

Supervised Machine Learning-Based Prediction of COVID-19

COVID-19 turned out to be an infectious and life-threatening viral disease, and its swift and overwhelming spread has become one of the greatest challenges for the world. As yet, no satisfactory vaccine or medication has been developed that could guarantee its mitigation, though several efforts and trials are underway. Countries around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely treatment. In this regard, healthcare experts, researchers and scientists have delved into the investigation of existing as well as new technologies. The situation demands development of a clinical decision support system to equip the medical staff ways to timely detect this disease. The state-of-the-art research in Artificial intelligence (AI), Machine learning (ML) and cloud computing have encouraged healthcare experts to find effective detection schemes. This study aims to provide a comprehensive review of the role of AI & ML in investigating prediction techniques for the COVID-19. A mathematical model has been formulated to analyze and detect its potential threat. The proposed model is a cloud-based smart detection algorithm using support vector machine (CSDC-SVM) with cross-fold validation testing. The experimental results have achieved an accuracy of 98.4% with 15-fold cross-validation strategy. The comparison with similar state-of-the-art methods reveals that the proposed CSDC-SVM model possesses better accuracy and efficiency.

Quantum cloud computing-a scientometric assessment of global research for the period 1999–2020

The study provides a quantitative and qualitative description of global quantum cloud computing research for the period 2000–2019, using metrics. The data for the study was sourced from Scopus database. During the period, the global research output in the subject totalled 459 publications, registered 39.63% annual average growth rate and 19.85 citations per paper. In addition, the study provides the distribution of global research output by country of publication, lists the top 10 most productive countries in the subject, identifies the leading research organizations as well as leading contributing authors in the subject. The study also provides the distribution of research output by major disciplines in order to bring out the most sought areas of research in quantum cloud computing. The study also identifies the most popular source journals in the subject. IEEE Access (10 papers), Physical Review Letters (6 papers) and Nature (4 papers) were found to be the most productive journals. Information Sciences, Science and Physical Review Letters were found to be the most impactful journals.

Mobile Cloud Computing Research – Issues, Challenges and Needs

With the rapid advance of mobile computing technology and wireless networking, there is a significant increase of mobile subscriptions. This drives a strong demand for mobile cloud applications and services for mobile device users. This brings out a great business and research opportunity in mobile cloud computing (MCC). This paper first discusses the market trend and related business driving forces and opportunities. Then it presents an overview of MCC in terms of its concepts, distinct features, research scope and motivations, as well as advantages and benefits. Moreover, it discusses its opportunities, issues and challenges. Furthermore, the paper highlights a research roadmap for MCC.

CollectionCare: an affordable service for the preventive conservation monitoring of single cultural artefacts during display, storage, handling and transport

In recent years there has been growing interest in the development of devices and software packages that allow museum decision-makers to manage the environmental conditions in collections and estimate the evolution of degradation of objects. A system able to monitor the environmental conditions but also to provide warnings and recommendations about failure boundaries would optimize conservation actions and strategies thus ensuring proper conservation of the collections in the long term.CollectionCare project aims to develop an innovative and affordable decision support system for the preventive conservation of cultural objects in small and medium-sized museums by combining research and technological advances in monitoring systems (sensor nodes), wireless communications, cloud computing, big data, and material degradation models.Validation and demonstration activities for the CollectionCare system will be carried out in six different European museums. To this end, communication efforts will be developed to promote the importance and applicability of these technologies in the conservation of cultural objects. All this in order to increase citizens’ awareness of the importance of preventive approaches for the conservation of the European cultural heritage.

Analysing the adoption of cloud computing service: a systematic literature review

Purpose The purpose of this paper is to presents an analysis of geographically and disciplinary scattered academic publications of cloud computing (CC) research in information systems. This review aims to understand the research methodology, research frameworks and models, geographical distribution, trends, critical factors and causal relationships associated with cloud computing adoption (CCA). Design/methodology/approach Systematic-literature-review using natural language processing is conducted to explore the phenomenon. The relevant research studies are extracted from various online databases using quality-assessment-criteria. Findings The study is a novel attempt to highlight the differences in critical factors for CCA in different country-settings. Further, the research explores the causal relationships among the identified factors. The findings of this 12-year systematic-review contribute by aiding the providers and potential adopters to devise context-specific strategies for the penetration of cloud services and sound adoption decisions (ADs), respectively. The findings also highlight the prospective avenues of research in the domain for researchers. Using the in-depth analysis, conceptual frameworks have been proposed that can assist in exploring the pre-adoption and post-adoption of CC. Originality/value This study contributes to CCA research by providing holistic insights into the methodology, research framework and models, geographical focus, critical factors and causal relationships influencing the AD or intention. The review highlights the unexplored emerging research topics in the field of CCA for future research directions.

Application and Research of Cloud Computing In Internet Processing

Application and Research of Cloud Computing In Internet Processing