• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.197-205
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• 1997

Manufacturers can meet the due dates of orders by using overtime, in which case, additional cost incurs for the amount of overtime. Although many studies have been reported on scheduling, only a few papers are founds on production scheduling using overtime. We consider the problem of production scheduling using overtime on a single machine, in which each job has a given due-date, a constant processing time. We assume that the daily overtime does not exceed the daily regular operation time. The objectives is to minimize the total overtimes, while meeting all due dates. We first present a mathematical model, and then suggest a heuristic algorithm for the problem.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2124-2126
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• 2008

In the wireless communication systems, the demand of multimedia services is also increased. Unlike typical data packets, realtime service such as VoIP packets have delay bound and low loss rate requirement. In this paper we propose a new scheduling algorithm that be able to allocate resources to the different kinds of services such as VoIP and data packet. The proposed algorithm considers both time delay and channel condition toe determine the priority. Simulation results show that the proposed algorithm works more efficiently than the conventional algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2824-2837
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• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.327-333
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• 2022

Wireless Sensor Networks (WSNs) plays an important role in our everyday life. WSN is distributed in all the places. Nowadays WSN devices are developing our world as smart and easy to access and user-friendly. The sensor is connected to all the resources based on the uses of devices and the environment [1]. In WSN, Quality of Service is based on time synchronization and scheduling. Scheduling is important in WSN. The schedule is based on time synchronization. Min-Max data size scheduling is used in this proposed work. It is used to reduce the Delay & Energy. In this proposed work, Two-hop neighboring node is used to reduce energy consumption. Data Scheduling is used to identify the shortest path and transmit the data based on weightage. The data size is identified by three size of measurement Min, Max and Medium. The data transmission is based on time, energy, delivery, etc., the data are sent through the first level shortest path, then the data size medium, the second level shortest path is used to send the data, then the data size is small, it should be sent through the third level shortest path.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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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.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1741-1751
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• 2007

The imprecise computation technique ensures that all time-critical tasks produce their results before their deadlines by trading off the quality of the results for the computation time requirements of the tasks. In the imprecise computation, most scheduling problems of satisfying both 0/1 constraints and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. In the previous studies, the reasonable strategies of scheduling tasks with the 0/1 constraints on uniprocessors and multiprocessors for minimizing the total error are proposed. But, these algorithms are all off-line algorithms. Then, in the on-line scheduling, NORA(No Off-line tasks and on-line tasks Ready upon Arrival) algorithm can find a schedule with the minimum total error. In NORA algorithm, EDF(Earliest Deadline First) strategy is adopted in the scheduling of optional tasks. On the other hand, for the task system with 0/1 constraints, NORA algorithm may not suitable any more for minimizing total error of the imprecise tasks. Therefore, in this paper, an on-line algorithm is proposed to minimize total error for the imprecise real-time task system with 0/1 constraints. This algorithm is suitable for the imprecise on-line system with 0/1 constraints. Next, to evaluate performance of this algorithm, a series of experiments are done. As a consequence of the performance comparison, it has been concluded that IOSMTE(Imprecise On-line Scheduling to Minimize Total Error) algorithm proposed in this paper outperforms LOF(Longest Optional First) strategy and SOF(Shortest Optional First) strategy for the most cases.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1048-1051
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• 1996

In this paper, we present real-time S/W architecture and techniques such as real-time scheduling, synchronization, and etc. for implementation of a real-time control system for driving multi-motors. Simulation shows feasibility of real-time S/W techniques presented here.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.7
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• pp.53-64
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• 2001

The gain-scheduling control technique is vary useful in the control problem incorporating time varying parameters which can be measured in real time. Based on these facts, in this paper the sway control problem of the pendulum motion of a container hanging on the trolly, which transports containers from a container ship to trucks, is considered. In the container crane control problem, suppressing the residual swing motion of the container at the end of acceleration, deceleration or the case of that the unexpected disturbance input exists is main issue. For this problem, in general, the trolley motion control strategy is introduced and applied. But, in this paper, we introduce and synthesize a new type of swing motion control system. In this control system, a small auxiliary mass is installed on the spreader. And the actuator reacts against the auxiliary mass, applying inertial control forces to the container to reduce the swing motion in the desired manner. In this paper, we assume that an plant parameter is varying and apply the gain-scheduling control technique design the anti-swing motion control system for the controlled plant. In this control system, the controller dynamics are adjusted in real-time according to time-varying plant parameters. And the simulation result shows that the proposed control strategy is shown to be useful to the case of time-varying system and, robust to disturbances like winds and initial sway motion.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.1
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• pp.31-40
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• 2012

Distributed arrival time control (DATC) is a distributed feedback control algorithm for real-time scheduling problems in dynamic operational environment. Even though DATC has provided excellent performance for dynamic scheduling problems, it can be improved by considering the following considerations. First, the original DATC heavily depends on the quality of initial solution. In this paper, well-known dispatching rules are incorporated DATC algorithm to enhance its performance. Second, DATC improves its solution with adjusting virtual arrival times of jobs to be scheduled in proportion to the gap between completion time and due date iteratively. Since this approach assigns the same weight to all gaps generated with iterations, it fails to utilize significantly more the latest information (gap) than the previous ones. To overcome this issue we consider exponential smoothing which enable to assign different weight to different gaps. Using these two consideration This paper proposes A-DATC (Advanced-DATC). We demonstrate the effectiveness of the proposed scheduling algorithm through computational results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.88-95
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• 2004

The previous disk scheduling schemes for best-effort applications do not guarantee the real-time requirement of multimedia objects and the real-time disk scheduling schemes do not satisfy throughput of multimedia server. So, this paper propose a two-step disk scheduling scheme to satisfy the requirement of best-effort as well as soft real-time applications. This scheme is based on the round robin algorithm that imposes different weights on the best-effort task and the real-time one. The experiment results on the Linux kernel have shown that both best-effort tasks and real-time tasks could get fair service.