• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.294-297
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• 2011

After Cloud Computing concept appeared in Google that is Internet search engine company and Famed online bookstore Amazon succeed in online rental business of computer resource, Global IT companies are watched by Cloud Computing. The companies applying Cloud Computing having been many changes, also domestic It business is throwing the spotlight on new paradigm of Cloud Computing. This paper is going to look at concept and trend of Cloud Computing, and describe situation and outlook of Cloud Computing in domestic companies.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.111-117
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• 2011

In this paper, proposed client virtualization technology to minimize degradation of the local computing environment, efficient and qualified users in the area of virtual functions needed to enable the user to provide important information in the local computing environment protection and performance, stability and continuity was important to keep. As well as the local computing environment from malicious code attacks such as methods for protecting virtualized domain also can not be overlooked as a major problem area in a virtualized, virtualized data through the encryption of user-space security, maximized. In addition, through virtualization using local computing resources efficiently while still a local computing system separate from the computing resources to a single user can get the same effect.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.20-30
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• 2013

An intelligent grid computing architecture is proposed and developed for transient stability constrained total transfer capability evaluation of future smart grid. In the proposed intelligent grid computing architecture, a model of generalized compute nodes with 'able person should do more work' feature is presented and implemented to make full use of each node. A timeout handling strategy called conditional resource preemption is designed to improve the whole system computing performance further. The architecture can intelligently and effectively integrate heterogeneous distributed computing resources around Intranet/Internet and implement the dynamic load balancing. Furthermore, the robustness of the architecture is analyzed and developed as well. The case studies have been carried out on the IEEE New England 39-bus system and a real-sized Chinese power system, and results demonstrate the practicability and effectiveness of the intelligent grid computing architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.53-56
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• 2008

Recently, the distributed system is being evolved into a new paradigm, named cloud computing, which provides users with efficient computing resources and services from data centers. Cloud computing would reduce the potential danger of Grid computing which utilizes resource sharing by constructing centralized data center. In this paper, a new data replication scheme is proposed for Hadoop distributed file system by changing 1:1 data transmission to 1:N. The proposed scheme considerably reduced the data transmission delay comparing to the current mechanism.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.736-739
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• 2012

Cloud Computing is attracting attention are activated and rapidly spread to companies and public institutions, etc. have been introduced are getting. Spotlighted these effects due to the utilization and integration of information system using cloud computing technology resources, and the resulting data security issue has been. In this paper, the side lights on due to the introduction of a cloud computing system, the resources of information systems, data security, and knowledge to provide the foundation for cloud computing infrastructure.

• 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 Broadcast Engineering
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• v.19 no.1
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• pp.24-30
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• 2014

This study investigates computing offloading effect of cloud in real-time video personal broadcast service, whose server is mobile device. Mobile device does not have enough computing resource for encoding video. The computing burden is offloaded to cloud, which has abundant resources in terms of computing, power, and storage compared to mobile device. By reducing computing burden, computation energy can be saved while transmission data amount increases because of decreasing compression efficiency. This study shows that the optimal operation point can be found adaptively to time-varying LTE communication condition result of tradeoff analysis between offloaded computation burden and increase in amount of transmitted data.

• 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.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.158-167
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• 2017

Internet-based social and interactive video applications have become major constituents of the envisaged applications for next-generation multimedia networks. However, inherently dynamic network conditions, together with varying user expectations, pose many challenges for resource allocation mechanisms for such applications. Yet, in addition to addressing these challenges, service providers must also consider how to mitigate their operational costs (e.g., energy costs, equipment costs) while satisfying the end-user quality of service (QoS) expectations. This paper proposes a heuristic solution to the problem, where the energy incurred by the applications, and the monetary costs associated with the service infrastructure, are minimized while simultaneously maximizing the average end-user QoS. We evaluate the performance of the proposed solution in terms of serving probability, i.e., the likelihood of being able to allocate resources to groups of users, the computation time of the resource allocation process, and the adaptability and sensitivity to dynamic network conditions. The proposed method demonstrates improvements in serving probability of up to 27%, in comparison with greedy resource allocation schemes, and a several-orders-of-magnitude reduction in computation time, compared to the linear programming approach, which significantly reduces the service-interrupted user percentage when operating under variable network conditions.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.1-8
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• 2010

In this paper, we propose a scheduling strategy for grid environment that reduces resource cost. This strategy considers resource cost and job failure rate to efficiently allocate local computing resources. The key idea of our strategy is that we use two-level scheduling using remote and local scheduler. The remote scheduler determines the expected total execution times of jobs using the current network and local system status maintained in its resource database and allocates jobs with minimum total execution time to local systems. The local scheduler recalculates the waiting time and execution time of allocated job and uses it to determine whether the job can be processed within the specified deadline. If it cannot finish in time, the job is migrated other local systems, through simulation, we show that it is more effective to reduce the resource cost than the previous Greedy strategy. We also show that the proposed strategy improves the performance compared to previous Greedy strategy.