• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1153-1170
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• 2012

Multimedia computing has attracted considerable attention with the rapid growth in the development and application of multimedia technology. Current studies have attempted to support the increasing resource consumption and computational overhead caused by multimedia computing. In this paper, we propose $MediaCloud$, a new multimedia computing paradigm that integrates the concept of cloud computing in handling multimedia applications and services effectively and efficiently. $MediaCloud$ faces the following key challenges: heterogeneity, scalability, and multimedia Quality of Service (QoS) provisioning. To address the challenges above, first, a layered architecture of $MediaCloud$, which can provide scalable multimedia services, is presented. Then, $MediaCloud$ technologies by which users can access multimedia services from different terminals anytime and anywhere with QoS provisioning are introduced. Finally, $MediaCloud$ implementation and applications are presented, and media retrieval and delivery are adopted as case studies to demonstrate the feasibility of the proposed $MediaCloud$ design.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.33-37
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• 2019

According to the enforcement of the Cloud Computing Development and User Protection Act, a new paradigm called as Cloud Computing is coming to the fore among public and private domestic enterprises. Therefore, domestic companies should develop SaaS products specialized for the domestic market and try to preempt the IaaS market ahead of global companies. Now we are facing a necessity to combine all the cloud systems in Korean government to operate seamlessly in a harmony. In this paper, we will look at the prospect of future development of related industry through cloud computing concept and G-cloud's cloud management system (G-CMS). G-CMS can be seen as the first system to comprehensively manage heterogeneous Unix virtualization systems. G-CMS can also save costs by managing heterogeneous virtualization systems in data centers.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.287-294
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• 2014

Cloud computing is a new method of computing and managing organizational information technology resources strategically. From the user perspective, it involves computing environment for accessing applications remotely, storing data, and supporting cooperative works. For the cloud computing to be effective in an organization, it should be accepted by individual users. In this paper we propose a research model, extending and modifying UTAUT model. We also test the validity of the model using the questionnaire from a sample of cloud computing services users.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.147-158
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• 2022

Cloud Computing offers flexible, on demand, ubiquitous resources for cloud users. Cloud users are provided computing resources in a virtualized environment. In order to meet the growing demands for computing resources, data centres contain a large number of physical machines accommodating multiple virtual machines. However, cloud data centres cannot utilize their computing resources to their total capacity. Several policies have been proposed for improving energy proficiency and computing resource utilization in cloud data centres. Virtual machine placement is an effective method involving efficient mapping of virtual machines to physical machines. However, the availability of many physical machines accommodating multiple virtual machines in a data centre has made the virtual machine placement problem a non deterministic polynomial time hard (NP hard) problem. Metaheuristic algorithms have been widely used to solve the NP hard problems of multiple and conflicting objectives, such as the virtual machine placement problem. In this context, we presented essential concepts regarding virtual machine placement and objective functions for optimizing different parameters. This paper provides a taxonomy of metaheuristic algorithms for the virtual machine placement method. It is followed by a review of prominent research of virtual machine placement methods using meta heuristic algorithms and comparing them. Finally, this paper provides a conclusion and future research directions in virtual machine placement of cloud computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.86-109
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• 2019

Cloud computing systems' performance is still a central focus of research for determining optimal resource utilization. Running several existing benchmarks simultaneously serves to acquire performance information from specific cloud system resources. However, the complexity of monitoring the existing performance of computing systems is a challenge requiring an efficient and interactive user directing performance-monitoring system. In this paper, we propose an effective multivariate control framework for monitoring cloud systems performance. The proposed framework utilizes the hardware cloud systems performance metrics, collects and displays the performance measurements in terms of meaningful graphics, stores the graphical information in a database, and provides the data on-demand without requiring a third party software. We present performance metrics in terms of CPU usage, RAM availability, number of cloud active machines, and number of running processes on the selected machines that can be monitored at a high control level by either using a cloud service customer or a cloud service provider. The experimental results show that the proposed framework is reliable, scalable, precise, and thus outperforming its counterparts in the field of monitoring cloud performance.

• Korea Information Processing Society Review
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• v.17 no.2
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• pp.18-29
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• 2010

In this paper, we surveyed SSO based security management including the knowledge domain of the area of cloud and its relevant components. Cloud computing refers to the delivery of software and other technology services over the Internet by a service provider. SSO refers to the ability to log on to a single security system once, rather than logging on separately to multiple security systems. Existing SSO solutions in cloud computing environment suggest several methods. SSO-based security Issues illustrate these key items in cloud computing environment such as risks and security vulnerabilities of SSO. SSO supports for multiple and different domains in cloud computing environment.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.538-549
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• 2019

Cloud computing is the concept of providing information technology services on the Internet, such as software, hardware, networking, and storage. These services can be accessed anywhere at any time on a pay-per-use basis. However, storing data on servers is a challenging aspect of cloud computing. This paper utilizes cryptography and access control to ensure the confidentiality, integrity, and proper control of access to sensitive data. We propose a model that can protect data in cloud computing. Our model is designed by using an enhanced RSA encryption algorithm and a combination of role-based access control model with extensible access control markup language (XACML) to facilitate security and allow data access. This paper proposes a model that uses cryptography concepts to store data in cloud computing and allows data access through the access control model with minimum time and cost for encryption and decryption.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.538-547
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• 2016

Cloud computing is a new style of computing in which dynamically scalable and reconfigurable resources are provided as a service over the internet. The MapReduce framework is currently the most dominant programming model in cloud computing. It is necessary to protect the integrity of MapReduce data processing services. Malicious workers, who can be divided into collusive workers and non-collusive workers, try to generate bad results in order to attack the cloud computing. So, figuring out how to efficiently detect the malicious workers has been very important, as existing solutions are not effective enough in defeating malicious behavior. In this paper, we propose a security protection framework to detect the malicious workers and ensure computation integrity in the map phase of MapReduce. Our simulation results show that our proposed security protection framework can efficiently detect both collusive and non-collusive workers and guarantee high computation accuracy.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• Convergence Security Journal
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• v.11 no.6
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• pp.31-36
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• 2011

Cloud computing is a system which efficiently utilizes resources. In this paper, we propose 2-factor authentication system combing PKI, ID_PW and location information. The proposed method improve the security of hybrid cloud systems and manage resources more safely.