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We present an overview of the history of forecasting software over the past 25 years, concentrating especially on the interaction between computing and technologies from mainframe computing to cloud computing. The cloud computing is latest one. For delivering the vision of various of computing models, this paper lightly explains the architecture, c...
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... The evolution of cloud computing technologies has been a pivotal aspect of the digital transformation era. Padhy and Patra (2012) provide an insightful overview of the historical progression of forecasting software, emphasizing the transition from mainframe computing to cloud computing. This evolution reflects the changing needs and capabilities in computing, where cloud computing has emerged as the latest model, offering enhanced flexibility and scalability. ...
... This evolution is marked by the critical roles played by major companies such as Salesforce, Amazon, Google, and Microsoft, which have been at the forefront of cloud computing advancements. Padhy and Patra (2012) also discuss the convergence of various IT paradigms to deliver the vision of cloud computing. This convergence has been essential in addressing the increasing volume of digital data and the need for efficient data processing and storage solutions. ...
... The evolution of cloud computing has also been influenced by the need for more efficient data storage and processing methods. Padhy and Patra (2012) note that the shift towards cloud computing has been driven by the limitations of previous computing models in handling the growing demands of data-intensive applications. Oludele et al. (2014) also explore the future of cloud computing, suggesting that ongoing advancements in virtualization technology will continue to shape the capabilities and applications of cloud computing. ...
In an era where data is the new gold, understanding the evolution and future trajectory of data storage technologies is crucial. This paper delves into the transformative journey from traditional storage methods to contemporary paradigms like cloud and edge computing, underpinned by the burgeoning influence of Big Data, IoT, AI, and machine learning. The study's aim is to provide a comprehensive analysis of these technologies, assessing their development, efficacy, and the challenges they face in meeting the escalating demands of data storage. The methodology employed is a meticulous synthesis of literature reviews, case studies, and comparative analyses. This approach facilitates an in-depth exploration of the historical evolution of data storage, the paradigm shifts from cloud to edge computing, and the interplay between technological advancements and user demands. The study also scrutinizes the security concerns inherent in these technologies and identifies strategic directions for future research. Key findings reveal that while cloud computing has revolutionized data storage with its scalability and flexibility, edge computing emerges as a vital solution to latency and bandwidth limitations. The integration of AI and machine learning is identified as a pivotal factor in enhancing the efficiency and intelligence of data storage systems. However, this integration presents unique challenges, necessitating innovative solutions. Conclusively, the study recommends a continued focus on innovation in data storage technologies, emphasizing the development of integrated, secure, and efficient solutions. Future research should particularly explore the potential of AI and machine learning in overcoming current limitations. The paper's scope encompasses a comprehensive overview of the current state and future potential of data storage technologies, making it a valuable resource for researchers, technologists, and policymakers in the field. Keywords: Data Storage Technologies, Cloud Computing, Edge Computing, Big Data, Internet of Things (IoT), Artificial Intelligence (AI).
... Additionally, there is an increasing need for all corporate software to be integrated in a low-cost, highly secure manner (Marston et al., 2011). As a result, cloud computing has evolved as a significant technical trend, spurred by the internet, which connects millions of computers (Padhy & Patra, 2012). Pay-as-you-go options, increased availability and adaptability, and cost savings are some of the most frequently cited advantages of cloud services. ...
p>This collection of nine essays examine the transformational process that businesses go through as they switch from outdated legacy systems to contemporary enterprise systems, emphasizing the value and importance of these cutting-edge technologies. The complexities of replacing legacy systems are covered in the first section, along with the drawbacks and advantages of the change. The next section of the article looks at the complexity of enterprise systems, highlighting their function in using ERP solutions to streamline and improve pertinent business operations. Additionally, it explores the ecosystem of ERP vendors, putting light on both technical and non-technical artifacts that help firms choose the best vendor. These essays also clarify the purpose of data collection, handling, and exposure in the context of business analytics, highlighting the crucial part that data intelligence plays in decision-making procedures. Additionally, it examines how the field of analytical methods is changing, showcasing the most recent trends and technological advancements. The essay also examines how business functions can be combined with business analytics, showing how firms can use analytics to improve operational effectiveness and acquire strategic insights. Finally, it illustrates the various ways that business analytics are used across various industries, highlighting the potential for securing advantageous opportunities and fostering sustainable growth. Finally, these essays emphasize the significance of using technological breakthroughs to achieve a competitive edge in the dynamic business landscape by studying the synergistic interaction between Enterprise systems and Business Analytics.</p
... Additionally, there is an increasing need for all corporate software to be integrated in a low-cost, highly secure manner (Marston et al., 2011). As a result, cloud computing has evolved as a significant technical trend, spurred by the internet, which connects millions of computers (Padhy & Patra, 2012). Pay-as-you-go options, increased availability and adaptability, and cost savings are some of the most frequently cited advantages of cloud services. ...
p>This collection of nine essays examine the transformational process that businesses go through as they switch from outdated legacy systems to contemporary enterprise systems, emphasizing the value and importance of these cutting-edge technologies. The complexities of replacing legacy systems are covered in the first section, along with the drawbacks and advantages of the change. The next section of the article looks at the complexity of enterprise systems, highlighting their function in using ERP solutions to streamline and improve pertinent business operations. Additionally, it explores the ecosystem of ERP vendors, putting light on both technical and non-technical artifacts that help firms choose the best vendor. These essays also clarify the purpose of data collection, handling, and exposure in the context of business analytics, highlighting the crucial part that data intelligence plays in decision-making procedures. Additionally, it examines how the field of analytical methods is changing, showcasing the most recent trends and technological advancements. The essay also examines how business functions can be combined with business analytics, showing how firms can use analytics to improve operational effectiveness and acquire strategic insights. Finally, it illustrates the various ways that business analytics are used across various industries, highlighting the potential for securing advantageous opportunities and fostering sustainable growth. Finally, these essays emphasize the significance of using technological breakthroughs to achieve a competitive edge in the dynamic business landscape by studying the synergistic interaction between Enterprise systems and Business Analytics.</p
... These stations were known as "inept terminals", and gave no dealing with power of their own. In light of everything, this sort of shared computational power is the fundamental, essential explanation of appropriated registering, and where everything began [5]. ...
This study comprehensively covers cloud computing; the diverse help models, its development, how could it be significant against the background of the arising Indian market and how might this innovation be tapped with the goal that its latent capacity is utilized to limit with regards to mechanical development in the country. Distributed computing as an idea has been around for a long while; however, the new years have seen it being used in different backgrounds considering the different benefits it has. India is bit by bit turning into the trail blazer being used and proliferation of cloud innovation. This research work targets laying out the essence of this innovation, the key qualities and to search for territories of progress where the innovation can be utilized and can be improved later on.
... (Zhou, 2018) divided the development stage of machine learning into the shallow learning stage , the deep learning stage (2006)(2007)(2008)(2009)(2010)(2011), and the outbreak stage (since 2012). (Padhy & Patra, 2012) To sum up, the previous division of AI industry development stage mostly focused on a specific subfield or a non-systematical set. The five stages of the HCC were fixed, which can not reveal the industry development history of a single technology. ...
This article aims to analyze the correlation status and development trend among science, technology and industry in the Artificial Intelligence (AI) subfield. First, it constructs the classification system and retrieval strategy for the AI subfield, and performs data cleaning and data finishing. Second, it designs the criteria and judgment method of the Industry Development Stages (IDS) in the AI subfield with the Delphi survey method. Third, it designs the monitoring method and model of the Science-Technology-Industry (STI) correlation with the methods of scientometrics and clustering, which involves three dimensions: science and IDS, technology and IDS, science & technology clustering and IDS; especially the monitoring with the global and national perspectives. Finally, it conducts empirical application in the field of neural network. The results illustrate that the correlation monitoring method can be conducive to grasp accurately the development opportunity and trend, the advantage subfield, and the development status of Science and Technology (S&T) for the dominant countries. The United States leads the global development in the empirical field. The proposed correlation monitoring method in this article can also be applied in other fields.
... Cloud Computing (CC) has been described in many studies in literature; for instance, [16] defined CC as a dynamic ICT paradigm, offering demand computing resources to use over a network infrastructure, while [17] referred to CC as a novel ICT form that is dependent on the virtualization and resources concept like hardware infrastructure, software, and data, disseminated via the Internet as a service model provided by the service provider. According to Padhy et al. [18], CC is a 5th generation computing following mainframe, personal computer, client-server computing and the Internet. Technically, Buyya et al. [19] proposed an approach concerning CC as a type of parallel and distributed system that comprises of a set of virtualized computers -a system which dynamically offers resources, with Service Level Agreement (SLA) agreed upon between the client and the service provider. ...
Cloud computing technology success has yet to develop from the infancy stage of implementation in the context of hospitals. This study primarily aimed to minimize the literature gap by examining the critical factors influencing cloud computing success in hospitals, particularly in Jordan. The study made use of online survey method for data collection, and the survey were distributed to chief information officers (CIOs) in the hospitals. Based on the obtained results, the inclusion of trust, networking quality and perceived risk into the information system model will contribute to the explanatory power of cloud computing success in Jordanian hospitals. In added, system quality, information quality, networking quality, service quality and trust were found to have a direct influence on cloud computing satisfaction, while risk was found to indirectly influence satisfaction via trust. Trust mediated the relationship between perceived risk and satisfaction. The proposed cloud computing success model is expected to assist hospitals in their evaluation and achievement of success following their cloud computing adoption in healthcare services.
... The whole setup for the request execution is the obligation of cloud service provider or cloud administration. [1] Progressively, any number of requests can be processed by the cloud and related software deal with the execution of all the assignments. So, related algorithm of load balancing should be used so that proper utilization of resources can be done [2]. ...
... A arquitetura baseada em mainframe surgiu em 1964, a partir do trabalho desenvolvido pela empresa IBM. No campo organizacional, o mainframe proporcionou um ganho na eficiência em processamento e armazenamento de dados, o que impactou na melhoria do planejamento de recursos e na obtenção de dados estatísticos sobre o consumo dos mesmos (Padhy & Patra, 2012). A grande desvantagem da arquitetura baseada em mainframe consistia nos custos tanto de aquisição, quanto de manutenção, que eram bastante elevados. ...
... Ahmad, N. (2017) has reviewed the major security issues in cloud and concluded that security is the major challenge in almost all the technologies concerned with the implementation of cloud. Not only the implementing technologies like virtualization and web services are lacking in security but the cloud architecture, SLA, and deployment model also requires proper security mechanism to win the trust of customer [15]. Sun, X. (2018) a survey was accomplished to review all critical security aspects of cloud computing less than three different parts viz. ...
... 5th Generation millimeter wave communications system is emerging as promising and potential wireless communication system having along with technologies like Cloud Computing, green communications, Internet of Things, Fog Commuting, device-to-device communications, Software defined millimeter wave and etc. 5th Generation millimeter wave communication system along with these technologies will provide high efficiency long term wireless communications system [1][2][3]. 5G millimeter wave communication system will fulfill the requirement of high data rates, low latency, low energy consumption, improved connectivity and reliability, High scalability and etc. 5G millimeter wave communication system still requires improved security mechanism and there is demand and need for efficient and optimum security in 5G communication system. To full-fill the demand and need of the 5G millimeter wave communication system in a flexible manner; several research has proposed to use flexible system where SDMW based technology can support in desirable and easy way [3][4][5]. ...
... CCE is useful for saving users, group users and organizations data and saves the cost and time. CCE allows user to access the files smoothly and allows organizations to function much simpler and easy manner by providing facility to access the data from anywhere in personal or public or group mode [1][2][3][4][5][6][7][8][9][10]. ...
A row column Diagonal (RCD) based data security method has been disused here for software defined millimeter wave (SDMW) based 5th generation (5G) millimeter wave (MW) communication system. The RCD based security method in this research paper discusses encryption and decryption technique for 5G SDMW based cloud computing environment (CCE) and fog computing environment (FCE). The Fog computing is an emerging technology trend and complementing along with Cloud computing. Fog Computing along with Cloud computing considers various emerging applications of ubiquitous computing, Internet of Flying-Things (IoT) and 5G millimeter wave (MW) communication system. FCE also provides data storage for user and groups at personal and professional level along with the application services. In this paper we are discussing, data security need and demand for Fog computing and Cloud computing. RCD based encryption and decryption module is very secure and useful. This proposed security method is easy to develop and integrate in SDMW based 5G millimeter wave (MWe) communications system. This research is promising high quality security for the 5G MW communications system to provide efficient and optimum security.
