• Informatization Policy
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• v.18 no.1
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• pp.24-44
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• 2011

The evolution of cloud computing over the past few years is potentially one of the major advances in information technology. However, if cloud computing is to achieve its potential, there needs to be a clear identification and understanding of the various issues involved, both from the perspectives of the providers and the consumers of the technology. While a lot of research is currently taking place in the technology itself, there is an equally urgent need for understanding the business-related issues surrounding cloud computing service. As more and more information on individuals and companies are placed in the cloud service, concerns are beginning to grow about just how safe and reliable an environment it is. For successful implementation of cloud services, it is necessary to establish the certification systems to ensure the safety and reliability of cloud services. This paper provides a safe and reliable framework for cloud service certification systems. In order to develop it, the critical issues related to service quality and certification of cloud services have been identified and the systematic framework for certification systems of cloud services and service provider domains have been developed. An evaluation method for the developed certification systems is also proposed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1267-1276
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• 2013

Cloud consumers who use cloud computing services are obliged to review and monitor the legal compliance of cloud providers who are consigned the processes of the PII (personally identifiable information) from them. This paper presented possible scenarios for cloud PII outsourcing and suggested PIMS (personal information management system) controls for outsourcing management between cloud consumers and cloud providers by analyzing both international standards and domestic certification schemes related to cloud computing and/or privacy management based on the legal obligations for PII outsourcing from Korean "Personal Information Protection Act (PIPA)". The controls suggested can be applicable for developing the guidance of complying with privacy laws in organizations or the checklist of PII outsourcing management in PIMS certification.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.155-160
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• 2013

The global recession circumstances, cloud computing has emerged as a new paradigm in the business IT sector. This paper explores the analysis of cloud service adoption Intension of Korean firms. Especially, we focus on Infrastructure as a Service (IaaS) among cloud services and apply TAM (Technology Acceptance Model) and VAM (Value-based Adoption Model) to analyze cloud service adoption intension The proposed exploratory model tests a number of hypotheses to understand the importance factors of IaaS adoption intension with TAM and VAM included additional cloud service characteristics such as scalability, agility, security, efficiency and reliability. Eventually, the findings of this study can not only help company users gain insights into IaaS adoption, but also help cloud service providers to develop their service effectively and improve marketing strategy in B2B cloud service market.

• ETRI Journal
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• v.32 no.4
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• pp.634-637
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• 2010

This letter presents a model for a dynamic collaboration (DC) platform among cloud providers (CPs) that prevents adverse business impacts, cloud vendor lock-in and violation of service level agreements with consumers, and also offers collaborative cloud services to consumers. We consider two major challenges. The first challenge is to find an appropriate market model in order to enable the DC platform. The second is to select suitable collaborative partners to provide services. We propose a novel combinatorial auction-based cloud market model that enables a DC platform among CPs. We also propose a new promising multi-objective optimization model to quantitatively evaluate the partners. Simulation experiments were conducted to verify both of the proposed models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4197-4219
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• 2017

Cloud computing is a new service to provide dynamic, scalable virtual resource services via the Internet. Cloud market is available to multiple cloud computing resource providers and users communicate with each other and participate in market transactions. However, since cloud computing is facing with more and more security issues, how to complete the allocation process effectively and securely become a problem urgently to be solved. In this paper, we firstly analyze the cloud resource allocation problem and propose a mathematic model based on combinatorial double auction. Secondly, we introduce a trust evaluation mechanism into our model and combine genetic algorithm with simulated annealing algorithm to increase the efficiency and security of cloud service. Finally, by doing the overall simulation, we prove that our model is highly effective in the allocation of cloud resources.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.59-65
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• 2012

The evolution of cloud computing service over the recent years is potentially one of the major advances in information and communication technology. However, if cloud computing service is to achieve its potential, there needs to be a clear understanding of the various issues such as service security, performance and availability and so on, both from the perspectives of the providers and the consumers of the cloud service. As more and more information on individuals, companies and public sectors are placed in the cloud service, concerns are beginning to grow about just how safe and reliable an environment it is. In order to overcome these situations, the Korea cloud service certification system and U.S. FedRAMP were performed in each country. This paper aims at comparing and analyzing between Korean cloud service certification systems and U.S. FedRAMP and describing the difference between them. Eventually, we propose the improvement strategy of Korea cloud service certification systems based on the comparison results between them.

• The Journal of Information Systems
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• v.30 no.3
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• pp.65-91
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• 2021

Purpose In this study, we investigated the impact of perceived risk and switching costs on switching intention to cloud service based on PPM (Pull-Push-Mooring) model. Design/methodology/approach We focused on revealing the switching factors of the switching intention to the cloud services. The switching factors to the cloud services were defined as perceived risk consisting of performance risk, economic risk, and security risk, and switching costs consisting of financial and learning costs. On the PPM model, we defined the pull factors consisting of perceived usefulness and perceived ease of use, and the push factor as satisfaction of the legacy system, and the mooring factor as policy supports. Findings The results of this study as follows; (1) Among the perceived risk factors, performance risk has a negative effect on the ease of use of pull factors, and finally it was found to affect the switching intention to the cloud services. Therefore, cloud service providers need to improve trust in cloud services, service timeliness, and linkage to the legacy systems. And it was found that economic risk and security risk among the perceived risk factors did not affect the switching intention to the cloud services. (2) Of the perceived risk factors, financial cost and learning cost did not affect the satisfaction of the legacy system, which is a push factor. It indicates that the respondents are positively considering switching to cloud service in the future, despite the fact that the respondents are satisfied with the use of the legacy system and are aware of the switching cost to cloud service. (3) Policy support was found to improve the switching intention to cloud services by alleviating the financial and learning costs required for cloud service switching.

• ETRI Journal
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• v.36 no.2
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• pp.197-205
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• 2014

This paper proposes a novel framework for virtual content delivery networks (CDNs) based on cloud computing. The proposed framework aims to provide multimedia content delivery services customized for content providers by sharing virtual machines (VMs) in the Infrastructure-as-a-Service cloud, while fulfilling the service level agreement. Furthermore, it supports elastic virtual CDN services, which enables the capabilities of VMs to be scaled to encompass the dynamically changing resource demand of the aggregated virtual CDN services. For this, we provide the system architecture and relevant operations for the virtual CDNs and evaluate the performance based on a simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4950-4966
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• 2015

Cloud providers now face the problem of estimating the amount of computing resources required to satisfy a future workload. In this paper, a virtual machine provisioning (VMP) mechanism is designed to adapt workload fluctuation. The arrival rate of forthcoming jobs is predicted for acquiring the proper service rate by adopting an exponential smoothing (ES) method. The proper service rate is estimated to guarantee the service level agreement (SLA) constraints by using a diffusion approximation statistical model. The VMP problem is formulated as a facility location problem. Furthermore, it is characterized as the maximization of submodular function subject to the matroid constraints. A greedy-based VMP algorithm is designed to obtain the optimal virtual machine provision pattern. Simulation results illustrate that the proposed mechanism could increase the average profit efficiently without incurring significant quality of service (QoS) violations.

• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.264-270
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• 2018

In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud.