• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.79-95
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• 2016

In order to improve the Quality-of-Service (QoS) of latency sensitive applications in next-generation cellular networks, multi-path is adopted to transmit packet stream in real-time to achieve high-quality video transmission in heterogeneous wireless networks. However, multi-path also introduces two important challenges: out-of-order issue and reordering delay. In this paper, we propose a new architecture based on Software Defined Network (SDN) for flow aggregation and flow splitting, and then design a Multiple Access Radio Scheduling (MARS) scheme based on relative Round-Trip Time (RTT) measurement. The QoS metrics including end-to-end delay, throughput and the packet out-of-order problem at the receiver have been investigated using the extensive simulation experiments. The performance results show that this SDN architecture coupled with the proposed MARS scheme can reduce the end-to-end delay and the reordering delay time caused by packet out-of-order as well as achieve a better throughput than the existing SMOS and Round-Robin algorithms.

• The Journal of Information Systems
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• v.13 no.2
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• pp.49-64
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• 2004

Recently, SCM(Supply Chain Management) embraces the dynamic environmental changes of the participatory bodies in supply chain. Under this dynamic SCM environment, the selection of supplier and outsourcing company is very important. In their selection, the productivity and expertise of suppliers and outsourcing companies are, of course, to be considered as important factors, but whether or nottheycanmeettheduedateisacritical factor. In particular, this is true because an order-based manufacture ought to have CTP(Capable To Promise). For this purpose, by capitalizing onthevirtualmanufactureundertheSCM, this paper has tried to suggest a new agent system for the selection of supplier and outsourcing company. While performing virtual manufacture based on the integration scheduling, this system acquires the production environment and scheduling information of both suppliers and outsourcing companies on a real-timebasis,thusmakingintegrationschedulingpossible. Also, in order to provetheviabilityofthisstudy,thispaper has selected a specific domain and applied it.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.523-533
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• 2006

We analyze two finite buffers queueing system with priority scheduling dependent upon queue length. Customers are classified into two types ( type-l and type-2 ) according to their characteristics. Here, the customers can be considered as traffics such as voice and data in telecommunication networks. In order to support customers with characteristics of burstiness and time-correlation between interarrival, the arrival of the type-2 customer is assumed to be an Markov- modulated Poisson process(MMPP). The service order of customers in each buffer is determined by the queue length of two buffers. Methods of embedded Markov chain and supplementary variable give us information for queue length of two buffers. Finally, performance measures such as loss and mean delay are derived.

• Journal of Power Electronics
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• v.11 no.4
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• pp.599-605
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• 2011

This paper proposes a gain scheduling method that improves the stability of grid-connected systems employing an LCL-filter. The method adjusts the current controller gain through an estimation of the grid impedance in order to reduce the resonance that occurs when using an LCL-filter to reduce switching harmonics. An LCL-filter typically has a frequency spectrum with a resonance peak. A change of the grid-impedance results in a change to the resonant frequency. Therefore an LCL-filter needs a damping method that is applicable when changing the grid impedance for stable system control. The proposed method instantaneously estimates the grid impedance and observes the resonant frequency at the same time. Consequently, the proposed method adjusts the current controller gain using a gain scheduling method in order to guarantee current controller stability when a change in the resonant frequency occurs. The effectiveness of the proposed method has been verified by simulations and experimental results.

• IE interfaces
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• v.6 no.2
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• pp.53-65
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• 1993

This paper deals with the development of a software module for production planning and scheduling activities of an existing Flexible Machining and Assembly System (FMAS). The Production Planning Module uses the hierarchical and sequential scheme based on "divide and conquer" philosophy. In this module, routes are determined based on the production order, orders are screened, tools are allocated, and order adjustments are executed according to the allocated tools. The Scheduling Module allocates the resources, determines the task priority and the start and completion times of tasks. Re-scheduling can be done to handle unforeseen situations such as lumpy demands and machine breakdowns. Since all modules are integrated with a central database and they interface independently, it is easy to append new modules or update the existing modules. The result of this study is used for operating the real FMAS consisting of a machining cell with 2 domestic NC machines and a part feeding robot, an assembly cell with a conveyor and 3 robots, an inspection cell, an AGV, an AS/RS, and a central control computer.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.7
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• pp.538-545
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• 2014

This paper proposes a coordinated multi-point (CoMP) based dynamic transmission scheme in a downlink multi-ship network, where a central ship selects a ship in order to maximize the utility function. The proposed scheduling scheme dynamically decides to the usage of the coordinated multi transmissions and selects a user to be served for every frame, in order to the utility function on the basis of the throughput and fairness. In particular, the proposed utilify function based scheduling scheme aims to increase the quality of service of ships at the edge of cells. Under the proportional fair scheduling, the simulation results show that the proposed utility function-based scheduling improves the throughput of the ships at the cell edge with the little sacrifice of the system capacity.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.367-372
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• 2013

Cloud computing technology has been developing at an increasing expansion rate. Today most of firms are using this technology, making improving the quality of service one of the most important issues. To achieve this, the system must operate efficiently with less idle time and without deteriorating the customer satisfaction. This paper focuses on enhancing the efficiency of a conventional Genetic Algorithm (GA) for task scheduling in cloud computing using Fuzzy Logic (FL). This study collected a group of task schedules and assessed the quality of each task schedule with the user expectation. The work iterates the best scheduling order genetic operations to make the optimal task schedule. General GA takes considerable time to find the correct scheduling order when all the fitness function parameters are the same. GA is an intuitive approach for solving problems because it covers all possible aspects of the problem. When this approach is combined with fuzzy logic (FL), it behaves like a human brain as a problem solver from an existing database (Memory). The present scheme compares GA with and without FL. Using FL, the proposed system at a 100, 400 and 1000 sample size*5 gave 70%, 57% and 47% better improvement in the task time compared to GA.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.40-48
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• 2009

In this article, scheduling of a casting sequence is studied in a casting foundry which must deliver products according to the Just-in-time(JIT) production policy of a customer. When a foundry manufactures a variety of casts with an identical alloy simultaneously, it frequently faces the task of production scheduling. An optimal casting schedule should be emphasized in order to maximize the production rate and raw material efficiency under the constraints of limited resources; melting furnaces and operation time for a casting machine. To solve this practical problem-fulfilling the objectives of casting the assigned mixed orders for the highest raw material efficiency in a way specified by the customer's JIT schedule, we implement simple integer programming. A simulation to solve a real production problem in a typical casting plant proves that the proposed method provides a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Employing this simple methodology, a casting foundry having an automated casting machine can produce a mixed order of casts with a maximum furnace utilization within the due date, and provide them according to their customer's JIT inventory policy.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.338-346
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• 2016

In order for the optimal solution of generators’ annual maintenance scheduling to be applicable to the actual power system it is crucial to incorporate the constraints related to the equivalent operation hours (EOHs) in the optimization model. However, most of the existing researches on the optimal maintenance scheduling are based on the assumption that the maintenances are to be performed periodically regardless of the operation hours. It is mainly because the computation time to calculate EOHs increases exponentially as the number of generators becomes larger. In this paper an efficient algorithm based on demand grouping method is proposed to calculate the approximate EOHs in an acceptable computation time. The method to calculate the approximate EOHs is incorporated into the optimization model for the maintenance scheduling with consideration on the EOHs of generators. The proposed method is successfully applied to the actual Korean power system and shows significant improvement when compared to the result of the maintenance scheduling algorithm without consideration on EOHs.