• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.758-759
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• 1995

In large-scale industry such as shipbuilding, aircraft manufacturing, and construction industry etc., it is required to consider two or three-dimensional spatial availability as one of bottlenecked resource constraints. We call this kind of scheduling a spatial scheduling, which considers the dynamic spatial layouts of objects as well as the traditional resource constraints. Since 1991, we have researched on the spatial scheduling for shipbuilding plant (Lee & Lee, 1992; Lee et al., 1994, Lee et al., 1995). In this paper, we present the various issues of spatial scheduling for the researchers and developers attacking spatial scheduling problems.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.370-375
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• 1992

This paper deals with the scheduling and simulation for FMC(Flexible Manufacturing Cells). In order to achieve CIM, there is a critical need to link factory level and machine level. The primary functions performed by this link for all jobs issued to the shop floor and cell include short-term scheduling and dynamic operational scheduling. Here, hierarchical control structure is introduced to define these functions. And Intelligent scheduling through expert module is adopted for efficiency of FMC operation. Computer simulation reveals that expert scheduling method is better than heuristics in various performance index.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.354-357
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• 1996

Virtual Manufacturing System(VMS) is an integrated computer based model which has physical, logical schema and behavior of real manufacturing system. In this paper, an integrated scheduling system is developed to simulate and control a Virtual Factory. A workflow model is constructed to define and analyze the structure of a VMS. On-line dynamic dispatching system is developed using MultiPass algorithm and scheduling system considering dynamic CAPP is carried out. Integrated scheduling system developed in this paper reduces the discrepancies between virtual model and real manufacturing system, and control of real shop floor is possible.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.81-84
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• 2000

Scheduling algorithm proposed in this paper is based on both DWRR(Dynamic Weighed Round Robin) method and QLT(Queue Length Threshold) method. The proposed scheduling algorithm guarantees delay property of realtime traffic, not considered in previous DWRR method, with serving realtime traffic preferentially by using RR(Round Robin) method which service each channel equally and QLT algorithm that is dynamic time priority method. Proposed cell scheduling algorithm may increase some complexity over conventional DWRR scheme because of delay priority based cell transmission method. However, due to reliable ABR service and congesition avoidance capacity, proposed scheduling algorithm has good performance over conventional DWRR scheme. Also, delay property based cell transmission method in proposed algorithm minimizes cell delay and requires less temporary buffer size

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.373-381
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• 2006

This paper considers a scheduling problem for a hybrid flowshop with dynamic order arrival. A hybrid flowshop is an extended form of a flowshop, which has serial stages like a flowshop but there can be more than one machine at each stage. In this paper, we propose a new method for the problem of scheduling with the objective of minimizing mean tardiness of orders which arrive at the shop dynamically. The proposed method is based on the list scheduling approach, however we use a more sophisticated method to prioritize lots unlike dispatching rule-based methods. To evaluate the performance of the proposed method, a simulation model of a hybrid flowshop-type production system is constructed. We implement well-known dispatching rules and the proposed methods in the simulation model. From a series of simulation tests, we show that the proposed methods perform better than other methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.7
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• pp.294-301
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• 2002

A new dynamic scheduling algorithm is proposed for CAN-based real-time system in this paper. The proposed algorithm is extended from an existing EDS(Earliest Deadline Scheduling) approach having a solution to the priority inversion. Using the proposed algorithm, the available bandwidth of network media can be checked dynamically, and consequently arbitration delay causing the miss of deadline can be avoided. Also, non-real time messages can be processed with their bandwidth allocation. Full network utilization and real-time transmission feasibility can be achieved through the algorithm. To evaluate the performance of algorithm, two simulation tests are performed. The first one is transmission data measurement per minute for periodic messages and the second one is feasibility in the system with both periodic messages and non-real time message.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1111-1116
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• 1993

In this study, we discuss the design of the expert system for the scheduling of the FMC(Flexible Manufacturing Cell) consisting of the several versatile machines. Due to the NP property, the scheduling problem of several machine FMC is very complex task. Thus we proposed the two heuritstic shceduling algorithms for solving the problem and constituted the algorithm based of solving the problem and constituted the algorithm base of ISS(Intelligent Scheduling System) using them. By the rules in the rule base, the best alternative among various algorithms in algorithm base is selected and applied in controlling the FMC. To show the efficiency of ISS, the scheduling output of ISS and the existent dynamic dispatching rule were tested and compared. The results indicate that the ISS is superior to the existent dynamic dispatching rules in various performance indexes.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.293-300
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• 2014

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.

• International Journal of Contents
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• v.8 no.4
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6B
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• pp.641-647
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• 2009

This paper proposes an improved predictive dynamic power management (DPM) scheme and a task scheduling algorithm to reduce unnecessary power consumption in embedded systems. The proposed algorithm performs pre-scheduling to minimize unnecessary power consumption. The proposed predictive DPM utilizes a scheduling library provided by the system to reduce computation overhead. Experimental results show that the proposed algorithm can reduce power consumption by 22.3% on the average comparing with the LLF algorithm for DPM-enable system scheduling.