• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.71-78
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• 2012

This research discusses the application of the control variables to achieve a more precise estimation for the target response in queueing network simulation. The efficiency of control variable method in estimating the response depends upon how we choose a set of control variables strongly correlated with the response and how we construct a function of selected control variables. For a class of queuing network simulations, the random variables that drive the simulation are basically the service-time and routing probability random variables. Most of applications of control variable method focus on utilization of the service time random variables for constructing a controlled estimator. This research attempts to suggest a controlled estimator which uses these two kinds of random variables and explore the efficiency of these estimators in estimating the reponses for computer network system. Simulation experiments on this model show the promising results for application of routing probability control variables. We consider the applications of the routing probability control variables to various simulation models and combined control variables using information of service time and routing probability together in constructing a control variable as future researches.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.3
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• pp.1-15
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• 1993

In this paper, we propose over-reporting avoidance scheme which avoids congestion of network traffics by adjusting managed system's over-reporting, on the OSI network management model which reports events from managed system to managing system. In case of reporting events from managed system to managing system, management traffic concentration occurs, and it causes over-loading on the managing system and congestion on the network. This scheme takes advantage of feedback from managing system to managed system. Managed system transmits event reports as much as maximum event pertime allocated to itself to managing system, and it sets it's management variables to LOCK state and stops event reports as Threshold time is reached. At the time, managing system directs event reports again by using M-set primitive with referring it's status. With this scheme, distributed processing, dynamic network adaptation, convergence of optimal operation point is possible. In addition to it, a fairness is assured. In order to detect characteristics of the Unary feedback over-reporting avoidance scheme. It is observed a control capability of the event reporting and fairness of each nodes through measuring. ThresholdTime value. It is measured a number of mean activating nodes and maintained time of LOCK state according to event reporting load, and also measured lost ratio of management packet, queuing delay in managing system, and goodput to observe effects of general packet load. Binary feedback scheme. Unary feedback overreporting avoidance scheme and raw scheme on the OSI network management system each are compared and analyzed, and finally proved that the scheme proposed in this study performs better.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.117-124
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• 2008

In this paper, the call setup performance of the CSCF(Call Session Control function) that manages the session control in providing the IMS(IP Multimedia subsystem)-based multimedia service in the BcN(Broadband convergence Network) is analyzed. While the performance related with the call/session of the SIP-Based voice service is analysed, the study for the call recessing performance of the IMS-based multimedia service is insufficient. In this paper, as, the processing capacity and subscriber number of CSCF were changed, the call setup delay time according to the session setup procedure of IMS was measured using the M/M/1 queuing model and OPNET simulation. The experimental results show that the sudden increased delay showed up in case the session establishment requirement ratio of total users over 13% of the CSCF processing capacity. Therefore, the user number and capacity of CSCF suitable for the session establishment delay threshold can be calculated or estimated.

• Journal of Korea Port Economic Association
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• v.23 no.2
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• pp.121-144
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• 2007

In general, the design of container yard and container handling system on container terminal are focused on operation of shipside than service about chassis from outside(C/O). It is not efficient for chassis from outside. The purpose of this paper is functional assessment of efficient container terminal and for higher performance of container terminal. first, the items which are concerned with container handling at the planning of container terminal are investigated and extracted through the practical data analysis of container terminal. Also, verified problems of planning and present condition through the functional assessment. Secondly, the improvements for container throughput in container yard are proposed and examined the effectiveness of improvements about queuing time of chassis from outside and service time of transfer crane by the evaluation decision model based upon multi criteria objectives.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.4
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• pp.105-112
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• 2022

Recently, many studies using reinforcement learning-based autoscaling have been performed to make autoscaling policies that are adaptive to changes in the environment and meet specific purposes. However, training the reinforcement learning-based Horizontal Pod Autoscaler(HPA) policy in a real environment requires a lot of money and time. And it is not practical to retrain the reinforcement learning-based HPA policy from scratch every time in a real environment. In this paper, we implement a reinforcement learning-based HPA in Kubernetes, and propose a transfer leanring technique using a queuing model-based simulation to accelerate the training of a reinforcement learning-based HPA policy. Pre-training using simulation enabled training the policy through simulation experience without consuming time and resources in the real environment, and by using the transfer learning technique, the cost was reduced by about 42.6% compared to the case without transfer learning technique.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.187-194
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• 2011

Optimizing truck dispatching-intervals is imperative in ready mixed concrete (RMC) delivery process. Intervals shorter than optimal may induce queuing of idle trucks at a construction site, resulting in a long delivery cycle time. On the other hand, intervals longer than optimal can trigger work discontinuity due to a lack of available trucks where required. Therefore, the RMC delivery process should be systematically scheduled in order to minimize the occurrence of waiting trucks as well as guarantee work continuity. However, it is challenging to find optimal intervals, particularly in urban areas, due to variations in both traffic conditions and concrete placement rates at the site. Truck dispatching intervals are usually determined based on the concrete plant managers' intuitive judgments, without sufficient and reliable information regarding traffic and site conditions. Accordingly, the RMC delivery process often experiences inefficiency and/or work discontinuity. Automatic data collection (ADC) techniques (e.g., RFID or GPS) can be effective tools to assist plant managers in finding optimal dispatching intervals, thereby enhancing delivery performance. However, quantitative evidence of the extent of performance improvement has rarely been reported to data, and this is a central reason for a general reluctance within the industry to embrace these techniques, despite their potential benefits. To address this issue, this research reports on the development of a discrete event simulation model and its application to a large-scale building project in Abu Dhabi. The simulation results indicate that ADC techniques can reduce the truck idle time at site by 57% and also enhance the pouring continuity in the RMC delivery process.

• Journal of the military operations research society of Korea
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• v.34 no.2
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• pp.163-174
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• 2008

The military is an organization where reliability and availability take much more importance than in any other organization. And, in line with a recent trend of putting emphasis on 'system readiness', not only functions but also availability of a weapon system has become one of achievement targets. In this regard, the military keeps spares for important facility and equipment, which is called as Maintenance Float (M/F), in order to enhance reliability and availability in case of an unforeseen event. The military has calculated yearly M/F requirements based on the number of equipment and utilization rate. However, this method of calculation has failed to meet the intended targets of reliability and availability due to lack of consideration on the characteristics of equipment malfunctions and maintenance unit's capability. In this research, we present an analysis model that can be used to determine an optimal M/F inventory level based on queuing and absorbed Markov chain theories. And, we applied the new analysis model to come out with an optimal volume of K-1 tank M/F for the OO division, which serves as counterattack military unit. In our view, this research is valuable because, while using more tractable methodology compared to previous research, we present a new analysis model that can describe decision making process on M/F level more satisfactorily.

• Safety and Health at Work
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• v.10 no.4
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.942-955
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• 2000

This paper proposes enhanced designs of global service logic and information flow for the mass-call based IN service, which increase call completion rates and optimize the resource in joint wired and wireless networks. In order to hanve this logic implemented, we design a Dynamic Queue Manager(DQM) applied to the call queuing service feature in the Service Control Point(SCP). In order to apply this logic to wireless service subscribers as well as wired service subscribers, the service registration flags between the Home Location Register(HLR) and the SCP are managed to notify the DQM of the corresponding service subscribers’ mobility. Hence, we present a dynamic queue management mechanism, which dynamically manages the service group and the queue size based on M/M/c/K queueing model as the wireless subscribers roam the service groups due to their mobility characteristics. In order to determine the queue size allocated by the DQM, we simulator and analyze the relationship between the number of the subscriber’s terminals and the drop rate by considering the service increment rate. The appropriate waiting time in the queue as required is simulated according to the above relationship. Moreover, we design and implement the DQM that includes internal service logic interacting with SIBs(Service Independent building Blocks) and its data structure.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.85-94
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• 2005

The scale and operating conditions of logistical systems very sensitively varies according to the variation of traffic intensity that is affected by the arrival characteristics of trucks and the attributes of loading/unloading services in logistics facilities. More exactly, logistics costs are incurred according to variations of traffic intensity. which are intimately linked with in a given time period. Also. although traffic intensity changes minutely, the range of cost variation is wide. Nevertheless, with regard to operating logistics systems, the existing studies make no attempt to analyze these factors. Therefore, it was the purpose of this study to determine the optimal traffic intensity to minimize excessive logistics costs resulting from the generation of unnecessary costs such as waiting costs and overcosts in operating a facility. For the purposes of this analysis. a determination model of optimal traffic intensity was constructed according to queuing theory. The inflow/outflow conditions of trucks and the terminal operational conditions were collected from an off-dock container terminal in Busan. On the basis of this data. the optimal traffic intensity that could off-set excessive waiting and operating costs was determined quantitatively. Also. using the optimal traffic intensity to be determined. we consider the improvements of operating system in the logistics facilities.