• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.80-88
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• 2001

The existed approaches to analyzing real-time schedulability take place exponential time and space complexity of this methods, since these uses a fixed priority scheduling and/or traverse all possible state spaces. This paper judges whether it is satisfied a given deadlines for real-time processes regarding a minimum execution time of process, periodic, deadline and a synchronizion time of processes by using the transaction rules of process algebra, and proposes a retrieval algorithm for unschedulable processes based on GUI environment. And we implement and evaluate the scheduling state analyzer that displays visually the result of schedulabiliy analysis for real-time processes.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.447-451
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• 2010

Monitoring and analyzing the status of smart objects, the ubiquitous smart monitoring system provides several information such as user-state index, service states and system operation among the services in real time. It also provides self-optimization and self-management for enhancing the performance of services. In order to expand the application scope of this real-time monitoring system, it is indispensible to process huge amount of stream data. In this paper, we propose a load balancing scheme to solve the overload of the monitoring agents. Our proposed scheme reduces deadline miss ratio of entire data by more than 80%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.117-124
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• 2008

Ultra-high voltage transformer industry has characteristic of small quantity batch production system by other order processing unlike general mass production systems. In this industry, observance of time deadline is very important in market competitive power security and company continued existence. The transformer winding is a process that rolls a coil is coated with an electric insulation material in order to generate the required voltage using the voltage fluctuation. The winding process is very important production process in the extra-high voltage transformer manufacturing industry because winding process is core process that occupy weight about half of whole process and is process that decide current ratio of transformer. This paper proposes a statistical calculation and control method of planned leadtime on the basis of real data and informations for the A company in transformer winding process. Moreover, we develop unit process scheduling system.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

• Journal of Computing Science and Engineering
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• v.4 no.3
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• pp.189-206
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• 2010

It is generally accepted that dynamic voltage scaling (DVS) is one of the most effective techniques of energy minimization for real-time applications in embedded system design. The effectiveness comes from the fact that the amount of energy consumption is quadractically proportional to the voltage applied to the processor. The penalty is the execution delay, which is linearly and inversely proportional to the voltage. According to the granularity of tasks to which voltage scaling is applied, the DVS problem is divided into two subproblems: inter-task DVS problem, in which the determination of the voltage is carried out on a task-by-task basis and the voltage assigned to the task is unchanged during the whole execution of the task, and intra-task DVS problem, in which the operating voltage of a task is dynamically adjusted according to the execution behavior to reflect the changes of the required number of cycles to finish the task before the deadline. Frequent voltage transitions may cause an adverse effect on energy minimization due to the increase of the overhead of transition time and energy. In addition, DVS needs to be carefully applied so that the dynamically varying chip temperature should not exceed a certain threshold because a drastic increase of chip temperature is highly likely to cause system function failure. This paper reviews representative works on the theoretical solutions to DVS problems regarding inter-task DVS, intra-task DVS, voltage transition, and thermal-aware DVS.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.783-791
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• 2006

In e-Trade, Real-Time System(RTS) plays a very important role. Each task is set with limited time, and appointed regulations must be followed because it can be greatly damaged if it cannot be executed in limited time. In e-Trade, the scheduling possibility techniques generally use periodical tasks; however, it is necessary to study more stable prediction scheduling possibility algorithm by using other task timing conditions and non-periodical task scheduling tasks. This study proposed an algorithm to increase the prediction possibility using individual task utilization rate, and presented scheduling possibility conditions using existing whole task utilization rate and the proposed algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.113-119
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• 2000

In this paper, we design and implement a query processor of real-time main memory database systems, which reflect the characteristics of main memory database systems and satisfy timing constraints. The proposed query processor manages real-time data that has timing constraint by exploiting meta database. It supports CLI in order to make application programs. It also supports extended CLI and stored CLI. The former can be expressed the Information on real-time transaction. The latter is designed to support frequently processed transaction. The proposed query processor is implemented as query processor of real-time database management systems. We Present performance evaluation results that illustrate ratio of transaction, which satisfy deadline are increased by the query processing ability of system and the efficient management of real-time data.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.194-203
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• 2005

The process of guaranteeing that a distributed real-time control system will meet its timing constraints, is referred to as schedulability analysis. However, schedulability analysis algorithm cannot be simply used to analyze the system because of complex calculations of algorithm. It is difficult for control engineer to understand the algorithm because it was developed in a software engineer's position. In this paper we introduce a Response-time Analysis Tool(RAT) which provides easy way far system designer to analyze the system by encapsulating calculation complexity. Based on the RAT, control engineer can verify whether all real-time tasks and messages in a system will be completed by their deadline in the system design phase.