• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.488-491
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• 2014

Based on a complete understanding research in Information and Communication Technologies (ICT), the Intelligent Transport Systems rapidly build up innovative applications to ensure real time attainment as well remote management of driven information, provide a huge range of services and involve many actors in automotive ecosystem. In this paper, we present an intelligent cloud computing for handling data received from traffic sensing technologies. Transportations technologies applied in ITS have played a great role in collecting data from devices deployed in vehicles and highway infrastructures utilizing broadband wireless technologies to the Cloud. In order to facilitate the interested in automotive industry to use data collected and afford services to the car's owner, a scalable acquisition, access to computing resources and offered services are the primary goal of the proposed cloud computing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.235-238
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• 2016

With the vision of Internet of Things (IoT), physical world itself is becoming a connected information system on the Internet and cyber world is computing as a physical act to sense and respond to real-world events collaboratively. The systems that tightly interlink the cyber and physical worlds are often referred to as Smart Systems or Cyber-Physical Systems. Smart IoT Clouds aim to provide a cyber-physical infrastructure for utility (pay-as-you-go) computing to easily and rapidly build, modify and provision auto-scale smart systems that continuously monitor and collect data about real-world events and automatically control their environment. Developing specifications for service interoperability is critical to enable to achieve this vision. In this paper, we bring an issue to extend Open Cloud Computing Interface for uniform, interoperable interfaces for Smart IoT Cloud Services to access services and build a smart system through orchestrating the cloud services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3219-3237
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• 2019

The Cloud Computing is growing rapidly in the current IT industry. Cloud computing has become a buzzword in relation to Grid & Utility computing. It provides on demand services to customers and customers will pay for what they get. Various "Cloud Service Provider" such as Microsoft Azure, Google Web Services etc. enables the users to access the cloud in cost effective manner. However, security, privacy and integrity of data is a major concern. In this paper various security challenges have been identified and the survey briefs the comprehensive overview of various security issues in cloud computing. The classification of security issues in cloud computing have been studied. In this paper we have discussed security challenges in cloud computing and also list recommended methods available for addressing them in the literature.

• The Journal of Information Systems
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• v.31 no.2
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• pp.63-88
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• 2022

Purpose The purpose of this study is to empirically analyze the factors affecting the intention to use cloud computing in the smart work environment. This study is meaningful in that it examines the characteristics of smart work and the fit of cloud computing characteristics, and it is a study that reveals the factors affecting the intention to use cloud computing by applying the integrated model of TTF and TAM. Design/methodology/approach In order to understand the factors affecting the intention to use cloud computing in the smart work environment, a research model that integrates TTF and TAM with the hypothesis was proposed. In order to verify the research hypothesis, this study conducted a survey on individuals with experience in smart work and cloud computing. And with the data 280 collected in the survey, path analysis was performed using the PLS structural equation. Findings As a result, it was found that task characteristics and technology characteristics had a positive (+) effect on task-skill fit, and task-skill fit had a positive (+) effect on perceived ease of use and usefulness. Also, task-skill fit, perceived ease of use, and perceived usefulness were found to have a positive (+) effect on intention to use.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.59-66
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• 2024

This paper presents the concept and characteristics of cloud computing, and it addresses how cloud computing delivers quality of service (QoS) to the end-user. Next, it discusses how to schedule one's workload in the infrastructure using technologies that have recently emerged such as Machine Learning (ML). That is followed by an overview of how ML can be used for resource management. This paper then looks at the primary goal of this project, which is to outline the benefits of using ML to schedule upcoming demands to achieve QoS and conserve energy. In this survey, we reviewed the research related to ML methods for predicting workloads in cloud computing. It also provides information on the approaches to elasticity, while another section discusses the methods of prediction used in previous studies and those that used in this field. The paper concludes with a summary of the literature on predicting workloads and optimising QoS in the cloud computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4087-4107
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• 2016

The current cloud computing paradigm is still vulnerable to a significant number of system failures. The increasing demand for fault tolerance and resilience in a cost-effective and device-independent manner is a primary reason for creating an effective means to address system dependability and availability concerns. This paper focuses on online failure prediction for cloud computing systems using system runtime data, which is different from traditional tolerance techniques that require an in-depth knowledge of underlying mechanisms. A 'failure prediction' approach, based on Cloud Theory (CT) and the Hidden Markov Model (HMM), is proposed that extends the HMM by training with CT. In the approach, the parameter ω is defined as the correlations between various indices and failures, taking into account multiple runtime indices in cloud computing systems. Furthermore, the approach uses multiple dimensions to describe failure prediction in detail by extending parameters of the HMM. The likelihood and membership degree computing algorithms in the CT are used, instead of traditional algorithms in HMM, to reduce computing overhead in the model training phase. Finally, the results from simulations show that the proposed approach provides very accurate results at low computational cost. It can obtain an optimal tradeoff between 'failure prediction' performance and computing overhead.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.1-22
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• 2016

While many organizations believe that cloud computing has the potential to reduce operational cost by abstracting capital assets like data storage center and processing systems into a readily on demand available and affordable operating expenses, still many of these organizations are not aware of the factors determining the performance of cloud computing technology. This paper provides a systematic literature review focusing on the factors determining the performance of cloud computing. In trying to come up with this review, the following sources were searched for relevant articles: ScienceDirect, Scientific.Net, ACMDigital Library, IEEE Xplore, Springer, World Scientific Journal, Wiley Online Library, Academic Search Premier (via EBSCOHost) and EdITLib (Education & Information Technology Digital Library). In first search strategy, approximately 100 keywords related to the research domain like; "Cloud Computing" and "Cloud Services" were used. In second search strategy, 65 keywords more related to the research domain were selected. In the third search strategy, the primary materials were identified and classified according to the paper types (Journal or Conference), year of publication and so on. Based on this study, twenty (20) factors were found that determine the performance of cloud computing. The IT organization needs to consider these twenty (20) factors in order to adopt cloud computing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.203-206
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• 2014

This paper discuss both cloud computing and smart computing, and then debates structural and functional issues about how the two computing systems interact for offering user-friendly information solutions. Smart Table is proposed to configure cloud resources. Smart Control algorithm is proposed to choose the best resources. The information interaction between cloud computing and smart computing services is realized for efficient construction of information systems and for user's convenience of information services.

• Journal of Korean Library and Information Science Society
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• v.43 no.1
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• pp.241-259
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• 2012

The purpose of this study is to identify the notion, types and best practices of cloud computing service through a literature review and to analyze the librarians' perceptions of cloud computing service on the basis of a survey. The survey sought to check the strengths and weaknesses of cloud computing service from librarians' perspectives and to find the specific areas where cloud computing service may be effective in libraries. Some key considerations in the application of cloud computing services to library systems are also suggested.

• The Journal of Information Systems
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• v.29 no.2
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• pp.197-220
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• 2020

Purpose Cloud computing that provides a new paradigm for a firm's use of information technology is getting a lot of attentions by practitioners. However, the empirical investigation on members of organizations using cloud computing are insufficient. Therefore, this study aims to examine the capabilities and perceptions of organizational members that should be considered important for successful cloud computing implementation. Design/methodology/approach This study proposed factors related to the capabilities and perceptions of members of the organization, and examined the relationship between these factors and successful cloud computing implementation and performance. In addition, this study tested the moderating effect of leadership and continuous supports through empirical analysis. The proposed hypotheses were verified through structural equation modeling using SmartPLS3.0 with the collected data. Findings The results showed that four factors except 'member behavior control' had a positive effect on successful cloud computing implementation, which had a positive effect on performance. In addition, leadership and organizational continuous support have been shown to strengthen the relationship among factors.