• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• International Journal of Contents
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• v.6 no.3
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• pp.15-18
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• 2010

Grid system is based on the Grid Security Infrastructure (GSI). GSI uses user's proxy to guarantee availability among multi-trust domains. Since grid system has been developed focusing on availability, GSI provides authentication and authorization performed by systems, but there are lacks of privacy consideration. For this reason, some researchers decide to use their own cluster system and do not want to use public grid systems. In this paper, we introduce a new privacy enhanced security mechanism for grid systems. With this mechanism, user can participate in resource allocation and authorization to user's contents more actively. This mechanism does not need to change previous middleware and minimize the computational overheads.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.317-318
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• 2022

본 논문에서는 클러스터 기반 엣지 모델에서 자원을 효율적으로 사용할 수 있는 지능형 엣지 자원 할당 정책 모델을 제안한다. 최근 쿠버네틱스 기반 클러스터 엣지 시스템 개발 연구 다양한 방향에서 진행 중이다. 따라서, 본 논문에서는 클러스터-엣지 모델 구조를 소개하고 이 모델에서 컴퓨팅 자원을 가진 워커에 컴퓨팅 오프로딩 서비스를 효율적으로 사용할 수 있는 최적의 지능형 클러스터-엣지 컴퓨팅 자원 정책을 생성하는 구조 및 알고리즘을 제안한다.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.461-470
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• 2005

This paper suggests a new policy for consolidating a company's profits by segregating the clients using the contents service and allocating the media server's resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) and profits through the cluster analysis of clients' data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.42-62
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• 2012

This paper suggests a genuine method to estimate the agglomeration effects of Industrial Cluster focusing on the FOODPOLIS (KOREA NATIONAL FOOD CLUSTER). In this study, we will focus on two issues related to the clustering effect. First, Clusters affect productivity, and a cluster allows companies to operate more productively in inputs; accessing technology, human resource, information, services, and needed institutions. Second, we assume that the effects of Industrial Cluster can be estimated from measurement on differency of an added value between large-scale enterprises and smaller ones. To demonstrate effectiveness of this approach, the estimated effect was compared with that from the related study (A Mini-Cluster). Industry Clusters have been considered as critical factors for regional competitiveness and economic revitalization. For this, the government and local government should find a way and strategy to provide useful contents that can attract the participation of firms and to secure strategic positioning and competition strategies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.3
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• pp.277-288
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• 2013

3GPP LTE-Advanced (Third Generation Partnership Project Long Term Evolution-Advanced) as a next generation mobile communication standard introduced small base stations such as femto cells or pico cells, and D2D (Device-to-Device) communications between mobiles in the proximity in order to satisfy the needs of rapidly growing wireless data traffic. A diverse range of topics has been studied to solve various interference situations which may occur within a single cell. In particular, an introduction of a small base station along with D2D communication raises important issues of how to increase the channel capacity and frequency efficiency in HetNets (Heterogeneous Networks). To this end, we propose in this paper methods to manage the interference between the macro cell and other small cells in the HetNet to improve the frequency efficiency. The proposed CCN (Cluster Coordinator Node)-assisted ICI (Inter-Cell Interference) avoidance methods exploit the CCN to control the interference in HetNet comprising of an MeNB (Macro enhanced Node-B) and a large number of small cells. A CCN which is located at the center of a number of small cells serves to avoid the interference between macro cell and small cells. We propose methods of resource allocation to avoid ICI for user equipments within the CCN coverage, and evaluate their performance through system-level computer simulations.

• Journal of Korean Society of Forest Science
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• v.99 no.4
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• pp.645-653
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• 2010

This study carried out the recognition of appropriate forest managements and directions in Jirisan National Park. For this purpose, we undertook interview survey about the recognition of forest management in Jirisan National Park from ecological and forest research fields' experts. From the statistical analysis results, it was founded that the difference among respondents' types was detected about recognition of forest management in National park. However, all the respondent types recognized that the forest management in National park is essential. So the forest management in national park by forest experts and relevant institutions are revealed needed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.5-6
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• 2019

Edge Computing에서 발생하는 데이터 분석에 대한 알고리즘의 성능 평가나 검증은 필수적이다. 이러한 평가 및 검증을 위해서는 비교 가능한 데이터가 필요하다. 본 논문에서는 Edge Computing에서 발생하는 데이터에 대한 분석 결과 및 Computing Resource에 대한 성능평가를 위해 Cloud 기반의 빅 데이터 분석시스템을 구축한다. Edge Computing 비교분석 빅 데이터 시스템은 실제 IoT 노드에서 Edge Computing을 수행할 때와 유사한 환경을 Cloud 상에 구축하고 연구되는 Edge Computing 알고리즘을 Data Analysis Cluster Container에 탑재해 분석을 시행한다. 그리고 분석 결과와 Computing Resource 사용률 데이터를 기존 IoT 노드 Edge Computing 데이터와 비교하여 개선점을 도출하는 것이 본 논문의 목표이다.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.45-49
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• 2022

The fourth industrial revolution, internet of things, and the expansion of online web services have increased an exponential growth and deployment in the number of cloud data centers (CDC). The cloud is emerging as new paradigm for delivering the Internet-based computing services. Due to the dynamic and non-linear workload and availability of the resources is a critical problem for efficient workload and resource management. In this paper, we propose the particle swarm optimization (PSO) based gated recurrent unit (GRU) neural network for efficient prediction the future value of the CPU and memory usage in the cloud data centers. We investigate the hyper-parameters of the GRU for better model to effectively predict the cloud resources. We use the Google Cluster traces to evaluate the aforementioned PSO-GRU prediction. The experimental shows the effectiveness of the proposed algorithm.

• Carbon letters
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• v.11 no.3
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• pp.176-183
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• 2010

PAN precursor fibers were produced via wet-spinning process, and effects of polymerization and spinning processes, especially the stretching process, were investigated on mechanical properties and micro-morphologies of precursor fibers. An increase in molecular weight, dope solid and densification and a decrease in surface defects were possible by controlling polymerization temperature, the number of heating rollers for densification and the jet stretch ratio, which improved the mechanical properties of precursor fibers. The curves for strength, modulus, tensile power and diameter as a function of stretch ratio can be divided into three stages: steady change area, little change area and sudden change area. With the increase of stretch ratio, the fiber diameter became smaller, the degree of crystallization increased and the structure of precursor fibers became compact and homogeneous, which resulted in the increase of strength, modulus and tensile power of precursor fibers. Empirical relationship between fiber strength and stretch ratio was studied by using the sub-cluster statistical theory. It was successfully predicted when the strengths were 0.8 GPa and 1.0 GPa under a certain technical condition, the corresponding stretch ratio of the fiber were 11.16 and 12.83 respectively.