• 컴퓨터교육학회논문지
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• 제9권6호
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• pp.89-98
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• 2006

최근 들어, 그리드 컴퓨팅 환경은 웹 서비스와 통합된 서비스 기반 그리드 컴퓨팅 환경으로 변화하고 있다. 이러한 구조에서의 그리드 어플리케이션은 워크플로우에 띠라 그리드 서비스가 수행되는 서비스 기반 그리드 어플리케이션이 되게 된다. 이것은 그리드 스케줄링 기법에서 그리드 서비스의 특징을 고려해야 한다는 것을 의미한다. 따라서 본 논문에서는 그리드 서비스의 가용성, 접근성, 신뢰성, 처리율, 감속속도에 바탕을 둔 그리드 서비스 성능 모델을 제안하고 서비스 기반 그리드 어플리케이션의 성능향상을 위해서 서비스 스케줄링 기법을 개발한다.

• 한국시뮬레이션학회논문지
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• 제21권2호
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• pp.59-67
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• 2012

그리드 컴퓨팅은 하나의 대용량 작업을 처리하도록 물리 자원을 구성하고 있지만 최근에는 데이터의 급속한 증가로 인해서 복수개의 작업을 처리하는 방법이 필요하다. 일반적으로 대용량 작업을 요청하면 각 물리 자원들이 작업을 분할하게 되며, 자원의 성능과 거리에 따라 처리 시간이 다르다. 성능에 따라 먼저 완료된 유효자원은 어떠한 작업도 하지 않으며, 모든 작업이 끝났을 경우에 다음 작업을 처리한다. 이에 본 논문에서는 먼저 처리가 완료된 자원을 다른 작업에 할당할 수 있는 동적 자원 재배치 스케줄링 모델(DRRSM: Dynamic Resource Reallocation Scheduling Model)을 제안한다. DRRSM은 먼저 처리가 완료된 자원을 다른 작업에 자원의 성능과 거리에 따라 작업을 재배치시키는 방법이다. DRRSM은 여러 개의 대용량 작업을 처리하는데 효과적이다.

• ETRI Journal
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• 제37권1호
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• pp.197-202
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• 2015

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day-ahead pricing strategy. Based on the Rubinstein-Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak-to-average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.

• Journal of Communications and Networks
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• 제18권3호
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• pp.484-492
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• 2016

Smart grid (SG) technology is now elevating the conventional power grid system to one that functions more cooperatively, responsively, and economically. When applied in an SG the demand side management (DSM) technique can improve its reliability by dynamically changing electricity consumption or rescheduling it. In this paper, we propose a new SG scheduling scheme that uses the DSM technique. To achieve effective SG management, we adopt a mixed pricing strategy based on the Rubinstein-Stahl bargaining game and a repeated game model. The proposed game-based pricing strategy provides energy routing for effective energy sharing and allows consumers to make informed decisions regarding their power consumption. Our approach can encourage consumers to schedule their power consumption profiles independently while minimizing their payment and the peak-to-average ratio (PAR). Through a simulation study, it is demonstrated that the proposed scheme can obtain a better performance than other existing schemes in terms of power consumption, price, average payment, etc.

• International Journal of Contents
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• 제6권3호
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• pp.19-24
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• 2010

Task scheduling is an integrated component of computing with the emergence of grid computing. In this paper, we address two different task scheduling models, which are static Round-Robin (RR) and dynamic Fastest Site First (FSF) task scheduling method, using extended timed marked graphs, which is a special case of Stochastic Petri Nets (SPN). Stochastic reward nets (SRN) is an extension of SPN and provides compact modeling facilities for system analysis. We build hierarchical SRN models to compare two task scheduling methods. The upper level model simulates task scheduling and the lower level model implements task serving process for different sites with multiple servers. We compare these two models and analyze their performances by giving reward measures in SRN.

• ETRI Journal
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• 제35권4호
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• pp.677-686
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• 2013

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real-time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost-effective way possible. In our research, to avoid the high peak-to-average ratio (PAR) of power, we combine the real-time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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• pp.131-135
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• 2009

This paper is the introduction of our work on distributed load scheduling in single-level tree network. In this paper, we derive a new calculation model in single-level tree network and show a closed-form formulation of the time for computation system. There are so many examples of the application of this technology such as distributed database, biology computation on genus, grid computing, numerical computing, video and audio signal processing, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권12호
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• pp.3096-3117
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• 2013

To execute the performance driven Grid applications, an effective and scalable workflow scheduling is seen as an essential. To optimize cost & makespan, in this paper, we propose a Scalable Cost-Time Trade-off (SCTT) model for scheduling workflow tasks. We have developed a heuristic algorithm known as Scalable Cost-Time Trade-off Scheduling (SCTTS) with a lower runtime complexity based on the proposed SCTT model. We have compared the performance of our proposed approach with other heuristic and meta-heuristic based scheduling strategies using simulations. The results show that the proposed approach improves performance and scalability with different workflow sizes, task parallelism and heterogeneous resources. This method, therefore, outperforms other methods.

• ETRI Journal
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• 제36권1호
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• pp.80-88
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• 2014

Recently, the idea of the smart grid has been gaining significant attention and has become a hot research topic. The purpose of this paper is to present a novel smart grid management scheme that uses game theory principles. In our proposed scheme, power appliances in the smart grid adaptively form groups according to the non-cooperative hedonic game model. By exploiting multi-appliance diversity, appliances in each group are dynamically scheduled in a cooperative manner. For efficient smart grid management, the proposed coopetition game approach is dynamic and flexible to adaptively respond to current system conditions. The main feature is to maximize the overall system performance while satisfying the requirements of individual appliances. Simulation results indicate that our proposed scheme achieves higher energy efficiency and better system performance than other existing schemes.

• 한국시뮬레이션학회논문지
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• 제15권3호
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• pp.1-9
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• 2006

현재 그리드 컴퓨팅은 네트워크 컴퓨팅 환경에서 대용량의 데이터와 엄청난 컴퓨팅의 문제를 해결하는데 매우 효과적인 해결책으로 각광받고 있다. 그리드는 애플리케이션을 여러 부분으로 나누어, 각 부분을 수많은 컴퓨터에서 동시에 수행함으로써 대규모 시뮬레이션 및 대용량 컴퓨팅을 실현할 수 있다. 그러나, 이를 위해서는 효과적인 자원 관리와 스케줄링 기법이 필요하다. 이 논문에서 우리는 분산된 그리드 컴퓨팅 환경에서의 자원관리와 스케줄링에 적용 가능한 그리드 거래망 모델을 제안하고 자율적인 자원 거래를 위한 가격 입찰 알고리즘을 소개한다. 우리는 모델의 효율성과 능력을 입증하기 위해 DEVSJAVA 모델링 & 시뮬레이션 환경 하에서 프로토타입 모델을 설계하고 실험하였다.