• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.75-85
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• 2012

In general, cellular network is deployed as distributed network architecture, so network equipment is spread out all over the coverage area. This case causes high cost. Recently, centralized network architecture has been deployable at cellular network since base station was able to be virtualized due to advance in computing power. The centralized network architecture in cellular network adjusts its cell radius dynamically and minimizes power consumption of the network. This paper introduces a new centralized deployment way of cellular network using SDR and cloud computing technology. Then, advantage and feasibility of the new network will be reviewed by implementing this novel network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.294-296
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• 2017

Cloud computing is a computing technique that uploads all the data from a cloud node to a cloud server and provides it to users as a service. This is difficult to provide services in real time depending on the network conditions. This is because it is necessary to download information to the remote site through the network, not the local area, and to download additional services to provide services in the cloud. So fog computing has been proposed as an alternative. In this paper, we propose an efficient data exchange technique between cloud, fog and user. The proposed fog provides services to users and collects and processes data. The cloud is responsible for the flow of data exchange and control between the fog. We propose a standard method for data exchange. The application for this is to process and service the information generated by the BAN (Body Area Network) in the fog, and the cloud serves as a mediator. This can resolve data heterogeneity between devices or services and provide efficient data movement.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.181-186
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• 2014

Web data mining aims at discovering useful knowledge from various Web resources. There is a growing trend among companies, organizations, and individuals alike of gathering information through Web data mining to utilize that information in their best interest. In science, cloud computing is a synonym for distributed computing over a network; cloud computing relies on the sharing of resources to achieve coherence and economies of scale, similar to a utility over a network, and means the ability to run a program or application on many connected computers at the same time. In this paper, we propose a new system framework based on the Hadoop platform to realize the collection of useful information of Web resources. The system framework is based on the Map/Reduce programming model of cloud computing. We propose a new data mining algorithm to be used in this system framework. Finally, we prove the feasibility of this approach by simulation experiment.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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• pp.299-305
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• 2020

We have developed a scheduler that additionally consider network performance by extending the Kubernetes developed to manage lots of containers in cloud computing nodes. The network delay adapt characteristics of the compute nodes were learned during server operation and the learned results were utilized to develop placement algorithm by considering the existing measurement units, CPU, memory, and volume together, and it was confirmed that the low delay network service was provided through placement algorithm.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.27-32
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• 2019

Along with the growth of u-Healthcare, we propose a security enhancement based on network separation for CloudHIS with for handling healthcare information to cope with cyber attack. To protect against all security threats and to establish clear data security policies, we apply desktop computing servers to cloud computing services for CloudHIS. Use two PCs with a hypervisor architecture to apply physical network isolation and select the network using KVM switched controller. The other is a logical network separation using one PC with two OSs, but the network is divided through virtualization. Physical network separation is the physical connection of a PC to each network to block the access path from both the Internet and the business network. The proposed system is an independent desktop used to access an intranet or the Internet through server virtualization technology on a user's physical desktop computer. We can implement an adaptive solution to prevent hacking by configuring the CloudHIS, a cloud system that handles medical hospital information, through network separation for handling security enhancement.

• 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.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1090-1100
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• 2021

Recently, as indoor activities increase due to the spread of infectious diseases, the metaverse is attracting attention. Metaverse refers to content in which the virtual world and the real world are closely related, and its representative platform technology is VR(Virtual Reality). However, since VR hardware is difficult to access in terms of cost, the concept of streaming-based cloud VR has emerged. This study proposes a server configuration and deployment method in an edge network when metaverse content involving multiple users operates based on cloud VR. The proposed algorithm deploys the edge server in consideration of the network and computing resources and client location for cloud VR, which requires a high level of computing resources while at the same time is very sensitive to latency. Based on simulation, it is confirmed that the proposed algorithm can effectively reduce the total network traffic load regardless of the number of applications or the number of users through comparison with the existing deployment method.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1041-1051
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• 2012

Attack on Cloud Computing, an intensive service solution using network infrastructure recently released, generates service breakdown or intrusive incidents incapacitating developmental platforms, web-based software, or resource services. Therefore, it is needed to conduct research on security for the operational information of three kinds of services (3S': laaS, PaaS, SaaS) supported by the Cloud Computing system and also generated data from the illegal attack on service blocking. This paper aims to build a system providing optimal services as a 4-stage defensive method through the test on the attack and defense of Cloud Computing services. It is a defense policy that conducts 4-stage, orderly and phased access control as follows: controlling the initial access to the network, controlling virtualization services, classifying services for support, and selecting multiple routes. By dispersing the attacks and also monitoring and analyzing to control the access by stage, this study performs defense policy realization and analysis and tests defenses by the types of attack. The research findings will be provided as practical foundational data to realize Cloud Computing service-based defense policy.