• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.651-657
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• 1998

In this study, an intelligent scheduling with hybrid architecture, which integrates expert system and neural network, is proposed. Neural network is trained with the data acquired from simulation model of FMC to obtain the knowledge about the relationship between the state of the FMC and its best dispatching rule. Expert system controls the scheduling of FMC by integrating the output of neural network, the states of FMS, and user input. By applying the hybrid system to a scheduling problem, the human knowledge on scheduling and the generation of non-logical knowledge by machine teaming, can be processed in one scheduler. The computer simulation shows that comparing with MST(Minimum Slack Time), there is a little increment in tardness, 5% growth in flow time. And at breakdown, tardness is not increased by expert system comparing with EDD(Earliest Due Date).

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.907-913
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• 2009

Pipeline construction is a highly repetitive and resource-intensive process that is exposed to various constraints and uncertainties in the working environment. Effective look-ahead scheduling based on the most recent project performance data can greatly improve project execution and control. This study enhances the traditional linear scheduling method with stochastic simulation to incorporate activity performance uncertainty in look-ahead scheduling. To facilitate the use of this stochastic method, a computer program, Stochastic Linear Scheduling Method (SLSM), was designed and implemented. Accurate look-ahead scheduling can help schedulers to better anticipate problem areas and formulate new plans to improve overall project performance.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1468-1473
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• 2009

Efficient communication of construction information has been critical for successful project performance. Building Information Modeling (BIM) has appeared as a tool for efficient communication. Through 3D CAD objects, it is possible to check interception and collisions of each object in advance. In addition, 4D simulation based on 3D objects integrated with time information makes it realize to go over scheduling and to perceive potential errors in scheduling. However, current scheduling simulation is still at a stage of animation due to manual integration of 3D objects and scheduling data. Accordingly, this study aims to develop an integrated model of 3D CAD objects that automatically creates scheduling information.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2005년도 춘계학술대회 논문집
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• pp.29-33
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes the service prediction-based job scheduling model and present its algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts a processing time of each processing component and distributes a job to processing component with minimum processing time. This paper implements the job scheduling model on the DEVSJAVA modeling and simulation environment and simulates with a case study to evaluate its efficiency and reliability Empirical results, which are compared to the conventional scheduling policies such as the random scheduling and the round-robin scheduling, show the usefulness of service prediction-based job scheduling.

• 한국통신학회논문지
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• 제18권9호
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• pp.1386-1394
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• 1993

지금까지 멀티미디어 정보 시스템에서 동기화를 해결하는 방식은 ad hoc 방식을 주로 사용하고 있으므로 멀티미디어 데이타의 동기화를 쉽고도 효율적으로 해결하기 위한 방법이 필요하다. 본 논문에서는, 모니터를 이용한 스케줄링 기법을 사용하여 미디어 데이타들 간의 동기화를 이루는 방식을 제안한다. 사용자가 고수준 사용자 인터페이스를 이용하여 미디어 데이타들 간의 시간 관계성을 표현하면, 시스템의 모니터는 특정한 시각에 수행하여야 할 미디어 데이타의 선정과 수행 시간을 제어하여 주며, 스케쥴러는 적절한 스케쥴링 방법을 결정하여 미디어 간의 동기화를 이루는 방식이다.

• 한국항해학회지
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• 제20권1호
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• pp.27-46
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• 1996

Vessles in the world merchant fleet generally operate in either liner or bulk trade. The supply and the demand trend of general cargo ship are both on the ebb, however, those trend of tankers and containers are in slight ascension. Oil tankers are so far the largest single vessel type in the world fleet and the tanker market is often cited as a textbook example of perfect competition. Some shipping statistics in recent years show that there has been a radical fluctuation in spot charter rate under easy charterer's market. This implys that the proper scheduling of tankers under spot market fluctuation has the great potential of improving the owner's profit and economic performance of shipping. This paper aims at developing the TS-DSS(Decision Support System for Tanker Scheduling) in the context of the importance of scheduling decisions. The TS-DSS is defined as the DSS based on the optimization models for tanker scheduling. The system has been developed through the life cycle of systems analysis, design, and implementation to be user-friendly system. The performance of the system has been tested and examined by using the data edited under several tanker scheduling scenarios and thereby the effectiveness of TS-DSS is validated satifactorily. The authors conclude the paper with the comments on the need of appropriate support environment such as data-based DSS and network system for succesful implementation of the TS-DSS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.551-569
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• 2024

With the rapid development of electric vehicles (EVs) industry, EV charging service becomes more and more important. Especially, in the case of suddenly drop of air temperature or open holidays that large-scale EVs seeking for charging devices (CDs) in a short time. In such scenario, inefficient EV charging scheduling algorithm might lead to a bad service quality, for example, long queueing times for EVs and unreasonable idling time for charging devices. To deal with this issue, this paper propose a Deep-Q-Network (DQN) based two-stage scheduling method for the large-scale EVs charging service. Fine-grained states with two delicate neural networks are proposed to optimize the sequencing of EVs and charging station (CS) arrangement. Two efficient algorithms are presented to obtain the optimal EVs charging scheduling scheme for large-scale EVs charging demand. Three case studies show the superiority of our proposal, in terms of a high service quality (minimized average queuing time of EVs and maximized charging performance at both EV and CS sides) and achieve greater scheduling efficiency. The code and data are available at THE CODE AND DATA.

• 한국인터넷방송통신학회논문지
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• 제18권1호
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• pp.15-21
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• 2018

데이터센터 네트워크의 자원을 효율적으로 활용하여 플로우들의 지연시간을 줄이기 위해서는 플로우 단위의 스케줄링보다는 패킷단위의 스케줄링이 적합하다. 따라서 최근에는 데이터센터 네트워크의 다중경로를 활용하여 패킷단위로 스케줄링을 수행하는 방식이 많이 제안되었다. 그러나 이로 인해 발생하는 순서 바뀐 패킷들이 표준 TCP 성능에 미치는 부정적인 영향을 줄이기 위해, 대부분의 방식들은 TCP 아래 계층에서 순서를 다시 맞추는 등의 보완방안을 필요로 한다. 본 논문에서는 데이터센터 네트워크의 대표적인 전송계층 프로토콜인 DCTCP가 다중경로상의 패킷단위 분산과 함께 사용될 때 어떤 성능을 보이는지 모의실험을 통해 조사한다. 모의실험 결과는 DCTCP가 큐의 길이를 짧게 유지할 수 있지만 혼잡신호에 따라 혼잡윈도우를 줄이는 방식 때문에 오히려 공평성 등의 측면에서는 기존 TCP보다도 낮은 성능을 가짐을 보여준다.

• 한국정보통신학회논문지
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• 제19권11호
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• pp.2665-2670
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• 2015

VANET은 차량들을 노드로 간주하는 에드혹 네트워크이고, 이들 노드들은 도로상에서 RSU들과 통신을 수행한다. VANET환경에서 요청한 데이터를 요청한 차량에게 정확하고 적절하게 전달하기 위해서는 스케쥴링이 매우 중요하다. 또한 차량이 해당 RSU 영역내에 존재할 때 차량이 요청한 데이터를 수신할 수 있게 하는 것이 중요하다. RSU는 스케쥴링 알고리즘에 따라 처리할 우선순위가 가장 높은 데이터를 선택한다. 본 논문에서는 RSU가 과부하 때문에 처리하지 못한 데이터를 다른 RSU로 전달되는 환경에서 우선순위가 제일 높은 요청 데이터를 선택할 수 있는 스케쥴링 알고리즘을 제안한다. 요청 데이터의 우선순위를 계산하기 위해 수정된 DBP 기법을 이용하였다. 시뮬레이션 결과 다양한 조건하에서 제안된 기법이 다른 스케쥴링 기법보다 성능이 우수함을 볼 수 있다.

• 한국시뮬레이션학회논문지
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• 제14권3호
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• pp.91-100
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes a service prediction-based job scheduling model and present its scheduling algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts the next processing time of each processing component and distributes a job to a processing component with minimum processing time. This paper implements the job scheduling model on the DEVS modeling and simulation environment and evaluates its efficiency and reliability. Empirical results, which are compared to conventional scheduling policies, show the usefulness of service prediction-based job scheduling.