• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.1-10
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• 2011

Recently, cloud computing which has provided enabling convenience that users can connect from anywhere and user friendly environment that offers on-demand network access to a shared pool of configurable computing resources such as smart-phones, net-books and PDA etc, is to be watched as a service that leads the digital revolution. Now, when business practices between departments being integrated through a cooperating system such as cloud computing, data streaming between departments is getting enormous and then it is inevitably necessary to find the solution that person in charge and find data they need. In previous studies the clustering simplifies the search process, but in this paper, it applies Hash Function to remove the de-duplicates in large amount of data in business firms. Also, it applies Bayesian Network of data mining for classifying the respect data and presents handling cloud computing based data. This system features improved search performance as well as the results Compared with conventional methods and CPU, Network Bandwidth Usage in such an efficient system performance is achieved.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.507-516
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• 2013

Mobile devices have limited computing power and resources. Since mobile devices are equipped with rich network connectivity, an approach to subscribe cloud services can effectively remedy the problem, which is called Mobile Cloud Computing (MCC). Most works on MCC depend on a method to offload functional components at runtime. However, these works only consider the limited verion of offloading to a pre-defined, designated node. Moveover, there is the limitation of managing services subscribed by applications. To provide a comprehensive and practical solution for MCC, in this paper, we propose a self-stabilizing process and its management-related methods. The proposed process is based on an autonomic computing paradigm and works with diverse quality remedy actions such as migration or replicating services. And, we devise a pratical offloading mechanism which is still in an initial stage of the study. The proposed offloading mechanism is based on our proposed MCC meta-model. By adopting the self-stabilization process for MCC, many of the technical issues are effectively resolved, and mobile cloud environments can maintain consistent levels of quality in autonomous manner.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.101-108
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• 2011

Climate change could have a pronounced impact on natural and agricultural ecosystems. To assess the impact of climate change, projected climate data have been used as inputs to models. Because such studies are conducted occasionally, it would be useful to employ Cloud computing, which provides multiple instances of operating systems in a virtual environment to do processing on demand without building or maintaining physical computing resources. Furthermore, it would be advantageous to use open source geospatial applications in order to avoid the limitations of proprietary software when Cloud computing is used. As a pilot study, Amazon Web Service ? Elastic Compute Cloud (EC2) was used to calculate the number of days with rain in a given month. Daily sets of climate projection data, which were about 70 gigabytes in total, were processed using virtual machines with a customized database transaction application. The application was linked against open source libraries for the climate data and database access. In this approach, it took about 32 hours to process 17 billion rows of record in order to calculate the rain day on a global scale over the next 100 years using ten clients and one server instances. Here I demonstrate that Cloud computing could provide the high level of performance for impact assessment studies of climate change that require considerable amount of data.

• 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.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.407-415
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• 2013

Recently, Interest variety of IT services and computing resources are increasing. As a result, the interest in the security of cloud environments is also increasing. Cloud environment is stored that to provide services to a large amount of IT resources on the Cloud. Therefore, Cloud is integrity of the stored data and resources that such as data leakage, forgery, etc. security incidents that the ability to quickly process is required. However, the existing developed various solutions or studies without considering their cloud environment for development and research to graft in a cloud environment because it has been difficult. Therefore, we proposed wire-wireless integrated Security management Model in cloud environment.

• Journal of KIISE
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• v.42 no.11
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• pp.1361-1371
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• 2015

Depending on the increase amongst various cloud services, the technology of the Cloud Service Broker (CSB) to find the most appropriate services to meet the needs of cloud service consumers has emerged. In order to advance for cloud services to be used through the CSB, it is important to ensure the quality level that meets the demands of consumers through a negotiation process based on the Service Level Agreement (SLA). However, quality metrics of cloud services are different from each other based on the measurement scale, which represents the quality level, and the calculation for each type of cloud services. Therefore, it is necessary to analyze the variability of the quality of cloud services and establish a SLA model for ensuring and improving the level of quality. In this paper, we analyze the quality metrics for the specific type of cloud services by applying the cross-cutting concept and propose a Virtual SLA (VSLA) meta-model.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.263-269
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• 2014

Mobile Cloud Service will provide cloud services through mobile devices. Because storage space constraints and computing process performance limitations of mobile devices, this service will process in the cloud environment after moving works and data that have to process in mobile terminal. The obstacles of mobile cloud service activity will have concerned high about the reliability service, data security, and the confidentiality security. In particular, in convergence of mobile services and cloud services, each threats are expected to be generated complicatedly. In this paper, we define the type of mobile cloud services as well as security threats that can occur in mobile cloud. Also we suggest security countermeasures in mobile app. and enterprises countermeasures. We suggest verification of mobile applications for user information protection about security countermeasures in mobile app. Also we describe the cloud providers responsibility and user responsibility about enterprises countermeasures.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.3
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• pp.247-270
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• 2019

The transition of the central government system to the cloud-based infrastructure is being conducted as the National Information Resources Service (NIRS, Ministry of the Interior and Safety) attempts to integrate government IT resources. In the early days, the transition was attempted as an infrastructure as a service (IaaS) for the cloud service of HW; however, currently, ithe transition is being converted to software as a service (SaaS) for the service of common business. Typical and common business is a document creation for government service and records management. Document creation is produced on cloud On-Nara system, and such system is deployed to central government agencies from 2015 to 2018, as well as the deployment to local government plans is to be gradually implemented after 2018. Currently, the records management is performed with the cloud RMS system, and such system is distributed to the central government from 2016 to 2018, as well as the dissemination to the local government is scheduled to be carried out, considering the adoption of the On-Nara system.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.105-117
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• 2010

In recent years, dynamic collaboration (DC) among cloud providers (CPs) is becoming an inevitable approach for the widely use of cloud computing and to realize the greatest value of it. In our previous paper, we proposed a combinatorial auction (CA) based cloud market model called CACM that enables a DC platform among different CPs. The CACM model allows any CP to dynamically collaborate with suitable partner CPs to form a group before joining an auction and thus addresses the issue of conflicts minimization that may occur when negotiating among providers. But how to determine optimal group bidding prices, how to obtain the stability condition of the group and how to distribute the winning prices/profits among the group members in the CACM model have not been studied thoroughly. In this paper, we propose to formulate the above problems of cooperative negotiation in the CACM model as a bankruptcy game which is a special type of N-person cooperative game. The stability of the group is analyzed by using the concept of the core and the amount of allocationsto each member of the group is obtained by using Shapley value. Numerical results are presented to demonstrate the behaviors of the proposed approaches.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.