• Journal of KIISE:Computing Practices and Letters
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• v.12 no.5
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• pp.275-285
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• 2006

This paper proposes an efficient market mechanism-based resource transaction model for grid computing. This model predicts the next resource demand of users and suggests reasonable resource price for both of customers and resource providers. This model increases resource transactions between customers and resource providers and reduces the average of transaction response times from resource providers. For prediction accuracy improvement of resource demands and suggestion of reasonable resource price, this model introduces a statistics-based prediction model and a price decision model of microeconomics. For performance evaluating, this paper measures resource demand prediction accuracy rate of users, response time of resource transaction, the number of resource transactions, and resource utilization. With 87.45% of reliable prediction accuracy, this model works on the less 72.39% of response time than existing resource transaction models in a grid computing environment. The number of transactions and the resource utilization increase up to 162.56% and up to 230%, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.988-990
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• 2005

본 논문에서는 그리드 컴퓨팅 환경에서 사용자와 자원 제공자간의 자원거래 시 사용자의 자원 요구량을 예측하고, 합리적인 가격 결정 알고리즘을 이용하여 기존의 자원 거래 모델에 비해 빠른 응답 속도를 갖는 모델을 제안한다. 본 논문에서 제안하는 모델은 사용자의 자원 요구량를 예측을 위해 통계학의 예측 모델을 적용하였고, 그리드 자원의 거래 가격 결정을 위한 경제학의 이론을 도입하였다. 우리는 실험을 통해 기존의 모델들과 비교하여 그리드 자원 거래를 위한 응답시간을 비교 하였다. 우리는 실험을 통해 기존의 모델들과 비교하여 응답시간이 최소 $72.39\%$ 향상된 결과를 얻었고 우리가 제안한 모델이 기존 모델에 비해 우수하다는 것을 입증하였다.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.11-21
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• 2006

Importance of and need for grid resource management have accelerated in accordance with increasing development of grid computing. However, it is very complex to distribute and utilize resources efficiently in geographically dispersed environments. This is due to the different access policies and constraints of grid resource owners. Users request resources according to their needs. Operators of a grid computing system need to be able to monitor the system states for reflecting these demands. So, a grid computing system needs a resource management policy that monitors states of resources and then allocates resources. This paper proposes a user demand-based grid trade management model that provides an efficient resource management by the trade allocation based on a users' demand and providers' supply strategy. To evaluate performance, this paper measures increasing rate of resource trades, average response time of trades, and processing time utilization. Firstly, the average increasing rates of trade are 585.7% and 322.6% higher than an auction model and a double auction model. Secondly, the average response time of the user demand-based grid trade management model is maintained between 3 and 5 simulation time. Finally, it is found that the processing time utilization is an average of 145.4% and 118.0% higher than an auction model and a double auction model. These empirical results demonstrate the usefulness of the user demand-based grid trade management model.

• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.1-10
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• 2014

A cloud computing is one of a parallel and distributed computing. The cloud computing provides some service for user with virtual resources. However, a user's service request does not show a time pattern. As a result, each resource also shows a different availability at the same time. This difference affects a quality of service (QoS) and a resource selection for users. Therefore, we propose the resource availability-based multi auction model for cloud service reservation and resource brokering system. The proposed system is to select the proper resource provider based on the users' request. The proposal adopts the multi phase of the auction to transact resources. The system evaluates the available factor of each resource on the auction phase, and finally reserves the service on the adaptive queue. The proposed model shows the better performance than other existing method.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.1-9
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• 2006

As an effective solution to resolve complex computing problems and to handle geographically dispersed data sets, grid computing has been noticed. Grid computing separates an application to several parts and executes on heterogeneous computing platforms simultaneously. The most important problem in grid computing environments is to manage grid resources and to schedule grid resources. This paper proposes a grid transaction network model that is applicable for resource management and scheduling in grid computing environment and presents a grid resource bidding algorithm for grid users and grid resource providers. Using DEVSJAVA modeling and simulation, this paper evaluates usefulness and efficiency of the proposed model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.754-757
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• 2000

인터넷을 이용한 사이버 거래가 빠른 속도로 증가함으로써 기업에게 있어 인터넷 쇼핑몰 구축은 더 이상 선택사항이 아닌 필수 사항이 되었다. 하지만 현재 사이버 거래 수준은 전통적 상거래 수준에 못 미칠뿐더러 거래 항목에 있어서도 매우 제한적인 것이 사실이다. 앞으로 사이버 거래는 계속적으로 증가하리라 전망되지만 제품의 특성 혹은 고객의 기호에 따라 전통적 상거래도 그 영역을 차지하며 함께 양립하여 발전할 것이다. 이에 본 연구에서는 기존의 상거래 시스템에 사이버 거래기능을 추가하는 모델을 제시한다. 먼저 지리적으로 멀리 떨어져 있는 유통망의 정보화를 위하여 인터넷 기술을 이용하고 공급체인(Supply Chain) 전체에 걸친 동기화를 위해 TOC(Theory of Constraint)의 DBR(Drum-Buffer-Rope) 스케줄링을 응용한다. 모든 생산 및 유통의 흐름 속도가 최종 분배 센타에 접수되는 고객의 요구에 따라 이루어지게 함으로써 공급체인 전체에 걸친 동기화를 이룰 수 있고 지속적인 버퍼 관리를 통하여서 재고의 절감은 물론 미출고의 발생도 최소화할 수 있다. 만약 분배 센타에 재고부족 현상이 일어날 경우에는 공급체인 상의 능력제약자원(Capacity Constraint Resource . CCR)을 찾아 개선 활동을 수행하며 공급체인의 흐름 속도를 능력제약자원에 맞추어 조절한다. 분배 센타에서 대리점 혹은 사이버 고객으로의 배송은 부분적 분할납품 Partial Transshipment : PT) 전략을 적용한다. 즉 각 분배 센타가 관리하는 수요지 중 인접한 지역을 부분적 분할납품 전략 적용 수요지로 선택하고 사이버 거래를 통해 생성된 물류가 부분적 분할납품 전략 적용 수요지에 분배되게 함으로써 각 분배 센타의 재고 완충역할을 수행하게 한다. 이에 따라 안전 재고 및 역 배송을 최소화 할 수 있을 뿐 아니라 미 출고로 인한 손실을 최소화하며 고객의 서비스를 일정하게 유지시킬 수 있을 것으로 기대된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.735-742
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• 2021

Recently, renewable energy-related power generation facilities have been surging due to the government's "Renewable Energy 3020", "Green New Deal", "2050 Carbon Neutrality" and "K-RE100" policies. Most renewable energy facilities are small and distributed, making it difficult to manage efficiently, and small distributed resources less than 1MW are having a hard time with participating in the market due to the limited sales and avoidance of trading. In particular, the intermittency of renewable energy has a significant impact on the stability of the power grid. The government is seeking to address volatility and intermittency issues through 'small distributed resource brokerage trading, and to expand the systematic resourceization and acceptability of heterogeneous large and small distributed resources. In this work, we intend to apply an AI-based power generation prediction model to a distributed resource brokerage trading system so that it can be utilized as a foundation platform for pioneering new energy business markets.

• The Journal of Society for e-Business Studies
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• v.8 no.3
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• pp.87-105
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• 2003

Business Process Management (BPM) is an emerging trend of managing business process life cycles and integrating heterogeneous systems . Recently, BPM is considered as an essential element for automation of complex business processes involving many companies, particularly for those in an e-Business environment. In such an environment, it is very important for each business partner to trace history of resources. However, it has been a difficult problem for Workflow Management Systems(WFMSs) to support management of resource changes because of limited storage, complex process structure, and absence of formal change model. In this paper. a new framework is proposed, which can support change management for documents, one of core resources of business process. Under a traditional WFMSs framework, all workflow components belong to either build-time or run-time function, and executions of workflow processes are performed by the two functions . To manage changes of documents while process executing. a new framework with additional component modules are required. A version control method is introduced for the purpose of managing document changes. The proposed method includes five models for document structure, process structure, association between process and document, version management, and efficient version storage. A prototype system is developed to demonstrate the effectiveness of the proposed models.

• Journal of IKEEE
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• v.23 no.3
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• pp.852-857
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• 2019

In order to manage the demand resources of project participants and to provide appropriate strategies in the virtual power plant's power trading platform for consumers or operators who want to participate in the distributed resource collective trading market, it is very important to forecast the next day's demand of individual participants and the overall system's electricity demand. This paper developed a power demand forecasting model for the next day. For the model, we used LSTM algorithm of deep learning technique in consideration of time series characteristics of power demand forecasting data, and new scheme is applied by applying one-hot encoding method to input/output values such as power demand. In the performance evaluation for comparing the general DNN with our LSTM forecasting model, both model showed 4.50 and 1.89 of root mean square error, respectively, and our LSTM model showed high prediction accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.491-493
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• 2021

최근 데이터 산업 발전과 함께 데이터를 저장, 공유, 거래가 가능한 다양한 데이터 저장소와 거래소가 증가하고 있다. 대부분의 데이터 저장소 및 거래소는 데이터 검색과 공유를 위해 DCAT 기반 메타데이터를 구성하고 있다. 하지만 DCAT 기반 메타데이터는 웹 검색 엔진에서 검색이 잘되지 않는 문제점을 가지고 있다. 이는 웹에서 자원을 출판하기 위한 데이터 모델 기법이 Schema.org 방법을 사용하고 있기 때문이다. 본 논문에서는 이런 문제점을 해결하기 위해 DCAT 기반 메타데이터를 Schema.org 방법으로 변환할 수 있는 새로운 기법을 제안한다. 제안하는 변환 기법은 데이터 저장소와 거래소 내 데이터셋이 웹에서 잘 검색될 수 있는 웹 출판 기능을 지원한다.