• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.95-100
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• 2022

Cloud computing platform is a shared pool of resources and services with various kind of models delivered to the customers through the Internet. The methods include an on-demand dynamically-scalable form charged using a pay-per-use model. The main problem with this model is the allocation of resource in dynamic. In this paper, we have proposed a mechanism to optimize the resource provisioning task by reducing the job completion time while, minimizing the associated cost. We present the Cooperative Agents Dynamic Resource Allocation and Monitoring in Cloud Computing CADRAM system, which includes more than one agent in order to manage and observe resource provided by the service provider while considering the Clients' quality of service (QoS) requirements as defined in the service-level agreement (SLA). Moreover, CADRAM contains a new Virtual Machine (VM) selection algorithm called the Node Failure Discovery (NFD) algorithm. The performance of the CADRAM system is evaluated using the CloudSim tool. The results illustrated that CADRAM system increases resource utilization and decreases power consumption while avoiding SLA violations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1129-1137
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• 2013

Cloud storage system that cloud computing providers provides large amounts of data storage and processing of cloud computing is a key component. Large vendors (such as Facebook, YouTube, Google) in the mass sending of data through the network quickly and easily share photos, videos, documents, etc. from heterogeneous devices, such as tablets, smartphones, and the data that is stored in the cloud storage using was approached. At time, growth and development of the globally data, the cloud storage business model emerging is getting. Analysis new network storage cloud storage services concepts and technologies, including data manipulation, storage virtualization, data replication and duplication, security, cloud computing core.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.201-209
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• 2021

The term, eGovernmen or e-Government, uses technology communications devices such as computers and the Internet to provide public services to citizens and others. The eGovernment or e-government provides citizens with new opportunities to access the government directly and conveniently, while the government provides citizens with directservices. Also, in these days, cloud computing is a feature that enables users to use computer system resources, especially data storage (cloud storage) and on-demand computing power, without having to manage themselves. The term is commonly used to describe data centers that are available to many users over the Internet. Today, the dominant Big Cloud is distributed across multiple central servers. You can designate it as an Edge server if it is relatively close to the user. However, despite the prevalence of e-government and cloud computing, each of these concepts has evolved. Research attempts to combine these two concepts were not being made properly. For this reason, in this work, we aim to produce independent and objective analysis results by separating progress steps for the analysis of e-government cloud service platforms. This work will be done through an analysis of the development process and architectural composition of the e-government development standard framework and the cloud platform PaaS-TA. In addition, this study is expected to derive implications from an analysis perspective on the direction and service composition of the e-government cloud service platform currently being pursued.

• Convergence Security Journal
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• v.13 no.1
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• pp.37-43
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• 2013

In 2010, the Ministry of National Defense decided to build a MegaCenter including the cloud computing technology by 2014, as part of the '2012 Information Service Plan', which is now underway. The Cloud computing system environment should be designed applying cloud computing technology and policy for an efficient infrastructure that many IT resources are available in the data center as a concentrated form. That is, the system should be designed in such a way that clouding services will be efficiently provided to meet the needs of users and there will not be unnecessary waste of resources. However, in order to build an optimal system, it should be possible to predict the service performance and the resource availability at the initial phase of system design. In this paper, using the CloudAnalyst simulator to predict availability of the K-defence cloud computing system service, conducts cloud modeling and analysis of the 'Facebook', one of the most famous social network service applications with most users in the world. An Optimal K-Defense cloud computing design model is proposed through simulation results.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.201-219
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• 2014

This paper considers service deployment and priority optimization for multiple service-oriented applications sharing reusable services, which are deployed as multiple instances in the cloud. In order to handle variations in the workloads of the multiple applications, service instances of the individual reusable services are dynamically provisioned in the cloud. Also service priorities for each application in a particular reusable service are dynamically adjusted. In this paper, we propose an analytic performance model, based on a queueing network model, to predict the expected sojourn times of multiple service-oriented applications, given the number of service instances and priority disciplines in individual reusable services. We also propose a simple heuristic algorithm to search an optimal number of service instances in the cloud and service priority disciplines for each application in individual reusable services. A numerical example is also presented to demonstrate the applicability of the proposed performance model and algorithm to the proposed optimal decision problem.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.877-884
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• 2013

As the Cloud Computing services are growing fast in the world, the number of Cloud Computing service users are being increased enormously in China. Studies on Intention-to-Use have been one of the interesting topics in the field of marketing. In this paper we investigate the factors influencing the intention-to-use of Cloud Computing services in China. Our research model is based on Technology Acceptance Model and includes 'privacy', 'information needs', 'service types', 'service appropriation', 'system quality', and 'system security'. We surveys the Chinese Cloud Computing service users and analyzes with Structural Equation Model. The results show that 'privacy', 'service appropriation', 'system quality', and 'system security' give positive effects to 'intention-to-use'. However, 'information needs' and 'service types' does not give positive effects.

• Informatization Policy
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• v.21 no.2
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• pp.49-66
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• 2014

In the last few years, cloud computing has grown from being a promising business concept to one of the fast growing segments of the IT industry. However, as more and more information on individuals and companies are placed in the cloud, concerns on just how safe the computing environment is have gradually increased. In this study, it will be explored if key characteristics of cloud computing services would affect the behavioral intention to use public cloud computing services. A conceptual model is developed and seven research hypotheses are proposed for empirical testing. The proposed model is examined through structural equation analysis. The results show that perceived risk has statistically significant effect on the privacy concern of users and the privacy concern has a negative influence on the trust. Finally, the trust has a positive effect on the attitude and the attitude has statistically significant effect on use intention. Implications of these findings are discussed for both researchers and practitioners and future research issues are raised as well.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.81-87
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• 2016

Cloud computing technologies are utilized and merged in various domains. Cloud computing technology-based personal cloud service technologies provide mobility and free access by using user centered storages and smart devices such like smart phones and table PCs. Therefore, we should overcome limits on the storage by solving the capacity problems of devices to provide security services in the personal cloud environments It can be addressable to provide the convenience of various security technologies. However, there are some security threats inherited from existing cloud environments and the possibilities of information leakage when devices are lost or stolen. Therefore, we designed a framework for providing secure cloud services by adding objects, such as user authorization, access tokens, set permissions by key generation, and key management assignments, for user management in personal cloud environments. We analyzed the stability of the proposed framework in terms of irreverent use and abuse, access to insiders, and data loss or leakage. And we evaluated the proposed framework in terms of the security with access control requirements in personal cloud environments.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.93-99
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• 2014

Cloud computing refers to borrow IT resources as needed by leveraging Internet technology and pay as much as you used by supporting real-time scalability depending on the service load. Virtualization which is the main technology of cloud computing is a technology that server, storage and hardware are regarded as not separate system but one system area and are allocated as needed. However, the security mechanisms provided by virtualized environments are difficult to cope with the traditional security mechanisms, having basic levels of visibility, control and audit function, on which the server is designed to monitor the traffic between the servers. In this paper, the security vulnerabilities of virtualization are analysed in the cloud computing environment and cloud virtualization security recommendations are proposed.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.