• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1114-1116
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• 2005

Shop floor control systems (SFCS) are used to make real-time planning and scheduling decisions to optimize the efficiency of manufacturing shops. These shops exhibit a non-linear, dynamic evolution caused by 1) the concurrent flows of disparate parts following complex routings, 2) a variety of machines that breakdown at random times, 3) stochastic arrivals of new parts with different priorities, and 4) jobs that have probabilistic processing times and transportation times. Because of their ability to capture that evolution faithfully, simulation models are often used in the aforementioned decisions. In this paper, various types of decision-making problems encountered in a shop floor have been investigated and categorized into process related problems and resource related problems for shop floor simulation.

• Journal of Korean Institute of Industrial Engineers
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• v.2 no.1
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• pp.85-92
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• 1976

In this paper, the employment planning model is developed which is a decision-making model for determining the optimum employment level with respect to varying net manpower requirement for each planing period such that total cost in a planning horizon is minimized. It is constructed as a nonlinear programming model and a dynamic programming model on the basis of studies in the areas of production smoothing and manpower scheduling. Costs for a planning period are categorized into regular wage cost, hiring cost, and overtime cost. The first is a linear function. The other two cost functions are of quadratic nature. The planning horizon of this planning model is intermediate range (five years) for which a fair planning accuracy can be guaranteed. The model considers learning period for each job class. It is simple and an optimum solution can be easily obtained by direct search techniques.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.1295-1298
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• 2001

멀티미디어 스트리밍 서비스를 제공하는 서버의 동적 부하분산을 위한 동적 가중치 기반 라운드 로빈 스케줄링 알고리즘을 제안한다. 기존의 가중치 기반 라운드로빈 알고리즘은 서버의 처리 용량만을 이용하여 가중치를 부여하므로 요청이 폭주할 경우 동적 부하 불균형을 갖게 된다. 동적 부하 불균형을 해결하기 위해 제안한 동적 가중치 기반 라운드로빈 알고리즘은 서버의 처리 용량뿐만 아니라 서버의 동적 부하를 이용하여 가중치를 부여하므로 동적 부하 불균형에 잘 적응하여 부하를 균형있게 조절한 수 있다. 제안한 알고리즘은 각 서버의 처리용량을 기준으로 가중치를 계산하고 동적으로 변하는 서버의 부하값에 가중치를 적용한다. 그 결과 동적 부하 불균형 문제를 해결했으며, 더 세밀한 부하 조절 기능을 수행할 수 있었다

• Korean Management Science Review
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• v.17 no.2
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• pp.125-134
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• 2000

Keeping the promised delivery date for a customer order is crucial for a company to promote customer satisfaction and generate further businesses. For this, a company should be able to quote the delivery date that can be achieved with the capacity available on the shop floor. In a dynamic make-to-order manufacturing environment, the problem of determining a delivery date for an incoming order with consideration of resource capacity, workload, and finished-product inventory can hardly be solved by an analytical solution procedure. This paper considers a situation in which a delivery date for a customer order is determined based on a job schedule, and presents the SimTriD algorithm that provides the best scheduling for determining a delivery date of customer order through the job schedule that efficiently utilizes manufacturing resources with consideration of interacting factors such as resource utilization, finished-product inventory, and due date.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.117-135
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• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.541-544
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• 2003

본 논문에서는 분산 실시간 멀티미디어 시스템에서 경성 실시간 태스크들과 멀티미디어 태스크들을 효율적으로 통합할 수 있는 동적 스케줄링 기법이 제시된다. 경성 실시간 태스크가 최악의 경우에 대한 실행 시간을 기반으로 하는 반면 멀티미디어 태스크는 평균 실행 시간을 기반으로 스케줄링된다. 동일한 시스템에 존재하는 두가지 태스크들에 대하여 CPU 대역폭을 분할하고 해당 대역폭의 비율을 동적으로 조정하는 스케줄링 기법을 제시함으로써 한 부류의 태스크들의 수와 도착 비율이 변동될 때 발생하는 과부하 문제를 해결할 수 있다 경성 실시간 태스크가 서버의 주기내에서 실행될 수 있는 시간이 제한되는 반면 멀티미디어 태스크에 설정된 대역폭은 동적으로 변할 수 있다 제시된 기법은 경성 실시간 태스크들의 실시간성을 모두 보장하는 한편 멀티미디어 태스크들의 평균 지연 시간을 최소화할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1B
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• pp.17-21
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• 2007

In this paper, we propose new on-line processor management algorithms that manage heterogeneous multimedia services while maximizing energy efficiency. These online management mechanisms are combined in an integrated scheme for higher system performance and energy efficiency. The most important feature of our proposed scheme is its adaptability, flexibility and responsiveness to current network conditions. Simulation results clearly indicate the superior performance of our proposed scheme to strike the appropriate performance balance between contradictory requirements.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.163-168
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• 2007

무선 모바일 환경에서 통신 장비의 에너지와 전송 대역폭의 제한을 해결하기 위하여 방송기법을 사용한다. 기존의 방송 스케줄링 방법들은 고정된 데이터 요청 빈도를 바탕으로 방송 스트림을 구성하기 때문에 사용자의 요구가 동적으로 변화하는 모바일 환경에서 활용하는 것은 비효율적이다. 또한 사용자의 우선순위를 고려하지 않음으로써 요청빈도가 낮은 데이터를 원하는 중요한 사용자가 오랜 시간 대기하는 상황이 발생할 수 있다. 본 논문에서 제안한 DNPS와 FPDNPS 방법은 실제 방송 청취를 시작한 사용자들의 프로파일 정보를 바탕으로 방송 스트림을 구성함으로써 동적인 변화를 반영할 분만 아니라, 사용자의 우선순위를 함께 고려함으로써 중요한 사용자의 대기시간을 줄일 수 있다. 또한 동시에 여러 개의 데이터를 요청하는 사용자들의 대기시간을 단축시키는 FPDNPS 알고리즘을 다중 채널환경으로 확장한 M-FPDNPS를 제안하고 실험을 통해 성능을 평가한다.

• Proceedings of the KIPE Conference
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• 2012.11a
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• pp.33-34
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• 2012

As the distributed power system with PV and ESS is highlighted to be one of the most prominent structure to replace the traditional electric power system, power flow scheduling is expected to bring better system efficiency. Optimal energy management system (EMS) where the power from PV and the grid is managed in time-domain using ESS needs an optimization process. In this paper, main optimization method is implemented using dynamic programming (DP). To overcome the drawback of DP in which ideal future information is required, prediction stage precedes every EMS execution. A simple auto-regressive moving-average (ARMA) forecasting followed by a PI-controller updates the prediction data. Assessment of the on-line optimal EMS scheme has been evaluated on several cases.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.3
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• pp.129-137
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• 2020

Kubernetes is one of the most widely used tool in cloud computing environments. It m anages POD as a basic operational unit, providing a isolated environments through container tech nology. Basically, its scheduler properly allocates POD, considering the utilizations of CPUs, mem ories and volumes on hosts. In our work, we develop a customized scheduling framework additio nally considering network resources. In the framework, we can monitor the dynamic variations of resources and make it possible to utilize the resources for the scheduler. This framework offers not only observing necessary information but also visualizing the data to scheduler for providing convenience.