• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.6
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• pp.559-565
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• 2016

For the purpose of the research, it is analyze the influence traffic Signal Progression on a CBD by expansion of Permissive Left-Turn on the advanced traffic management system program compared with traffic response control For this, divided a average distance between intersections, a traffic network on five district in four city. As the result, Volume of the traffic management system on a advanced traffic management system program compared with traffic response control is effective in traffic signal cycle 160sec 286car per lane, in 140sec 308car, 120sec 264car. As well, for a traffic network as the length of a traffic network 2.0~3.0km, under 2.0km, all of traffic signal cycle(160sec, 140sec, 120sec) a passing band and stop is more effective. But the traffic management system on traffic response control compared with the traffic management system on a advanced traffic management system program is effective in the length of a traffic network over 5.0km. For the efficiency of traffic signal system manage, it should be runned the traffic management system on traffic response control in addition to the traffic management system on a advanced traffic management system program on CBD. As the result of simulation the business in chungju-si, the travel speed of the traffic management system on a advanced traffic management system program is 41.2km/h and the travel speed of traffic response control is 37.5km/h. Therefore, it should be runned per length of a traffic network the traffic management system on traffic response control in addition to the traffic management system on a advanced traffic management system program on CBD.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.81-95
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• 1987

In line with the continued growth of car ownership, the traffic problems in central area of metropoles such as Seoul would become increasingly degraded. comparing with most western cities, the problems in Seoul are characterized by the improportionately high rates of intersection delay, station congestion, traffic accidents caused by weaving conflicts and pedestrian congestion. It is caused by the lack of flexibility I street network, which is prerequisite for upholding the efficacy of traffic management and control, resulted from the simplicity of network graph in terms of connectivity, street density and distribution by width. This pattern has been resulted from the prolonged policy pursuing the street-widening of the nagging bottleneck in such a short period since the 1950s, comparing that most western cities had undergone over several centuries an age of horse-and-vehicle transportation. In order to improve the expected traffic problems in central area over the coming periods of motorization, it is imperative to restructure the street network in Central Seoul so that the efficacy of traffic management and control may be operative. Based upon the long-range planning the street network should be restructured by stages so that cenral traffic may be controled by one-way operation and most through-traffic be detoured around fringe area.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.472-478
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• 2017

In this paper, we deals with optimizing traffic signal timing in grid networks by using a network topology design method. Optimizing traffic signal timing includes minimizing delay time delay between departure and destination by interlocking straight traffic signal in the minimum spanning tree(MST). On the assumption that users of network abide by the paths provided in this paper, this paper shows optimizing traffic signal timing in grid networks. the paths provided in this paper is gathered by using Dijkstra algorithm used in computer networks. The results indicate minimizing delay time of passing through the grid network and interlocking traffic signal in the grid network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.416-420
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• 2002

Traditional queueing analyses are very useful for designing a network's capacity and predicting there performances, however most of the predicted results from the queueing analyses are quite different from the realistic measured performance. And recent empirical studies on LAN, WAN and VBR traffic characteristics have indicated that the models used in the traditional Poisson assumption can't properly predict the real traffic properties due to under estimation of the long range dependence of network traffic and self-similarity In this parer self-similar characteristics over statistical approaches and real time network traffic measurements are estimated It is also shown that the self- similar traffic reflects network traffic characteristics by comparing source model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.772-776
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• 2005

To support abruptly increasing data traffic in these days, network management is needed. And also to maintain the steady infra, there is MPLS need which can support traffic engineering. It's necessary that MPLS doesn't only manage network to support recently booming data traffic, but has capacity to support traffic engineering to keep static infrastructure. Traffic engineering, method that a large-scale user shifts traffic to the beforehand designated routes that pass through specific nodes on network, is operation that is mapping traffic flow to the physical network topology. In this paper, we supplement the defect of the traditional RSVP traffic engineering and to construct far more steady infra, we suggest the way of its development of ERSVP signaling protocol.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.104-107
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• 2002

Traditional queueing analyses are very useful for designing a network's capacity and predicting there performances, however most of the predicted results from the queueing analyses are quite different from the realistic measured performance. And recent empirical studies on LAN, WAN and VBR traffic characteristics have indicated that the models used in the traditional Poisson assumption can't properly predict the real traffic properties due to under estimation of the long range dependence of network traffic and self-similarity. In this paper self-similar characteristics over statistical approaches and real time network traffic measurements are estimated. It is also shown that the self-similar traffic reflects network traffic characteristics by comparing source model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.105-108
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• 2005

To support abruptly increasing data traffic in these days. network management is needed. And also to maintain the steady infra, there is MPLS need which can support traffic engineering. It's necessary that MPLS doesn't only manage network to support recently booming data traffic, but has capacity to support traffic engineering to keep static infrastructure. Traffic engineering, method that a large-scale user shifts traffic to the beforehand designated routes that pass through specific nodes on network, is operation that is mapping traffic flow to the physical network topology. In this paper, we supplement the defect of the traditional RSVP traffic engineering and to construct far more steady infra, we suggest the way of its development of ERSVP signaling protocol.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1931-1936
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• 2007

Demand forecasting for railroad traffic is fairly important to establish future policy and plan. The future demand of railroad traffic can be predicted by analyzing the demand of air, marine and bus traffic which influence the demand of railroad traffic. In this study, forecasting the demand of railroad traffic is implemented through neural network using the demand of air, marine and bus traffic. Estimate accuracy of the demand of railroad traffic was shown about 84% through neural net model proposed.

• Journal of Communications and Networks
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• v.12 no.6
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• pp.624-631
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• 2010

Effective traffic matrix estimation is the basis of efficient traffic engineering, and therefore, quality of service provision support in IP networks. In this study, traffic matrix estimation is investigated in IP networks and an Elman neural network-based traffic matrix inference (ENNTMI) method is proposed. In ENNTMI, the conventional Elman neural network is modified to capture the spatio-temporal correlations and the time-varying property, and certain side information is introduced to help estimate traffic matrix in a network accurately. The regular parameter is further introduced into the optimal equation. Thus, the highly ill-posed nature of traffic matrix estimation is overcome effectively and efficiently.