• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.79-87
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• 2007

The interchanges of urban freeways have many problems with traffic operation due to high off-ramp flows and frequent congestion at adjacent intersections. The flow exiting from off-ramps is affected by the operational status and traffic volume conditions of the nearest signalized intersection. As a result, off-ramp flow cannot exit and the queue backs up the freeway mainline when queues from the signalized intersection form up to the junction of the off-ramp and street. The spacing between an off-ramp and an adjacent intersection is likely to determine the traffic conditions at the adjacent intersection. However, the current design guidelines do not consider such a factor. This study is to develop a model calculating the spacing between off-ramps and adjacent intersections considering the signal, traffic, and road conditions. The variables affecting the model in this study are effective green time (g/C), volume-capacity ratio (v/c), the number of lanes, and off-ramp volume. Various scenarios are designed to represent the effects of the variables and the road networks are constructed using VISSIM, which is a common traffic micro-simulation software package. The queue length is derived from VISSIM and this length is considered as the recommended spacing between the off-ramp and the adjacent intersection. Through the simulation analysis, regression models are developed to calculate the queue length reflecting the various conditions such as signals, traffic, and road configurations. The developed model can be used to create road design guidelines to determine the location of off-ramps in the planning stage.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.159-166
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• 2004

The capacity concept presented in the Highway Capacity Manual is for steady-state traffic flow assuming that there is no restriction in downstream flowing, which is traditionally used for planning, design, and operational analyses. In the congested traffic condition, the control objective should be to keep the congested regime from growing and to recover the normal traffic condition as soon as possible. In this control case, it is important to predict the spatial-temporal pattern of congestion evolution or dissipation and to estimate the throughput reduction according to the spatial-temporal pattern. In this context, the new concept of dynamic capacity for managing congested traffic is developed in terms of spatial-temporal evolution of downstream traffic congestion and in view of the 'input' concept assuming that flow is restricted by downstream condition rather than the 'output' concept assuming that there is no restriction in downstream flowing (e.g. the mean queue discharge flow rate). This new capacity is defined as the Maximum Sustainable Throughput that is determined based on the spatial-temporal evolution pattern of downstream congestion. And the spatial-temporal evolution pattern is estimated using the Newell's simplified q-k model.

• Journal of Korean Society of Transportation
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• v.7 no.2
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• pp.89-111
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• 1989

This study concentrates on a basic investigation research related to some of parameters to be used for the analysis of capacity and the level of service for signalized intersections. The parameters to be studied are ideal saturation flow rate, large vehicle's passenger car equivalent(PCE) ane the lane utilization factors of through and left turn vehicles. The field data were collected at six intersections in Seoul using video cameras so as to reflect conditions in urban areas. In this study discharge headway based on a rear bumper of each vehicle was used and all the parameters were estimated using a regression technique. The findings of this research are as follows : 1. The saturation headway and saturation flow rate on a single lane with the lane width of 3.1m are 1.652 seconds and 2,180 pcphgpl. It was found that the frist 5 vehicles in the queue experience some start-up lost time. 2. It was confirmed that the new method adopted for the estimate of large vehicle's PCE gives larger PCE values than those derived from the method commonly used. 3. For the estimate of lane utilization factors of through and left turn vehicles, a relationship was established and the corresponding formulas were developed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.1-11
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• 2013

This research proposed integrated expressway traffic management strategy using ramp metering and toll mainline metering. This research suggested a traffic signal optimization model for integrated operation of ramp and mainline metering based on Demand-Capacity Model that is used to optimize allowable input volume for ramp metering in FREQ model. The objective function of this model is sectional throughput volume maximization, and this model can calculate optimal signal timings for mainline metering and ramp metering. This study conducted an effectiveness analysis of integrated metering strategy using PARAMICS and its API. It targeted Seoul's Outer Ring Expressway between Gimpo and Siheung toll gate. As a simulation result, integrated operation of mainline and ramp metering provided more smooth traffic flow, and throughput volume of mainline increased to 14% in congested section. In addition, a queue of 400 meter was formed at metering point of toll gate. This research checked that integrated traffic management strategy facilitates more efficient traffic operation of mainline and ramp from diffused traffic congestion.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.141-143
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• 2019

Vessel Traffic Service (VTS) increases the efficiency of maritime traffic in terms of reducing marine accidents and the efficient use of port facilities. This means that ports and waterways have their own capacities and can be safely adapted to their capacity through proper traffic management of the VTS. Proper traffic management can reduce the number of vessels and unnecessary waiting in ports, which can lead to economic benefits of ups and port terminals. On the other hand, Korean ports and waterways have restrictions on the maximum speed for safety, but there is no restriction on the minimum speed. However, ships that operate at low speeds in ports and waterways may be able to occupy long periods of operational routes, which may impede efficient port operation. Therefore, the purpose of this study is to propose the minimum speed of ship for efficient port and waterway use. To this end, we reviewed the current laws and systems and proposed the appropriate minimum speed in the waterway using the theory of queue.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.55-63
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• 2019

This paper develops an algorithm to determine the batch size of the batch process in real time for improving production and efficient control of production system with multiple processes and batch processes. It is so important to find the batch size of the batch process, because the variability arising from the batch process in the production system affects the capacity of the production. Specifically, batch size could change system efficiency such as throughput, WIP (Work In Process) in production system, batch formation time and so on. In order to improve the system variability and productivity, real time batch size determined by considering the preparation time and batch formation time according to the number of operation of the batch process. The purpose of the study is to control the WIP by applying CONWIP production system method in the production line and implements an algorithm for a real time batch size decision in a batch process that requires long work preparation time and affects system efficiency. In order to verify the efficiency of the developed algorithm that determine the batch size in a real time, an existed production system with fixed the batch size will be implemented first and determines that batch size in real time considering WIP in queue and average lead time in the current system. To comparing the efficiency of a system with a fixed batch size and a system that determines a batch size in real time, the results are analyzed using three evaluation indexes of lead time, throughput, and average WIP of the queue.

• 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 the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.31-39
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• 1999

A new approximation method for finding the steady-state probabilities of the number of customers present in queueing systems with Poisson arrivals and two servers with different deterministic service times with infinite waiting room capacity is developed. The major assumption made for the approximation is that the residual service times of the servers have mutually independent uniform distributions with densities equal to the reciprocals of the respective service times. The method reflects the heterogeneity of the servers only through the ratio of their service times, irrespective of the actual magnitudes and difference. The transition probability matrix is established and the steady-state probabilities are found for a variety of traffic intensities and ratios of the two service times; also the mean number of customers present in the system and in the queue, and server utilizations are found and tabulated. The method was validated by simulation and turned out to be very sharp.

• Journal of Digital Convergence
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• v.6 no.2
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• pp.117-125
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• 2008

High-volume web sites often use clusters of servers with load balancing as a way to increase the performance, scalability, and availability of the sites. Load balancing, usually performed by load balancer in front of such clusters, is a technique to spread workload between several computers or resources, in order to get optimal resource utilization or response time. In this paper we examine the performance for several configurations of cluster-based web servers using a simulation approach. We investigate two types of buffering scheme (common and local) for web clusters and three load balancing policies (uniformly random, round robin, and least queue first), using response time as a performance measure. We also examine two basic approaches of scaling web clusters: adding more servers of same type or upgrading the capacity of the servers in the clusters.