• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2573-2589
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• 2023

As 5G mobile systems carry multiple services and applications, numerous user, and application types with varying quality of service requirements inside a single physical network infrastructure are the primary problem in constructing 5G networks. Radio Access Network (RAN) slicing is introduced as a way to solve these challenges. This research focuses on optimizing RAN slices within a singular physical cell for vehicle-to-everything (V2X) and enhanced mobile broadband (eMBB) UEs, highlighting the importance of adept resource management and allocation for the evolving landscape of 5G services. We put forth two unique strategies: one being offline network slicing, also referred to as standard network slicing, and the other being Online reinforcement learning (RL) network slicing. Both strategies aim to maximize network efficiency by gathering network model characteristics and augmenting radio resources for eMBB and V2X UEs. When compared to traditional network slicing, RL network slicing shows greater performance in the allocation and utilization of UE resources. These steps are taken to adapt to fluctuating traffic loads using RL strategies, with the ultimate objective of bolstering the efficiency of generic 5G services.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.175-181
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• 2005

Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits at a wide range of scales-Self-similarity. Self-similarity is expressed by long term dependency, this is contradictory concept with Poisson model that have relativity short term dependency. Therefore, first of all for design and dimensioning of next generation communication network, traffic model that are reflected burstness and self-similarity is required. Here self-similarity can be characterized by Hurst parameter. In this paper, when different many data traffic being integrated under various environments is arrived to communication network, Hurst Parameter's change is analyzed and compared with simulation results.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.205-215
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• 2008

As static traffic assignment has reached its limitation with ITS policy applications and due to the increase of interest in studies of ITS policies since the late 1980's, dynamic traffic assignment has been considered a tool to overcome such limitations. This study used the Dynameq program, which simulates route choice behavior by macroscopic modeling and dynamic network loading and traffic flow by microscopic modeling in consideration of the feasibility of the analysis of practical traffic policy. The essence of this study is to evaluate the feasibility for analysis in practical transportation policy of using the dynamic traffic assignment technique. The study involves the verification of the values estimated from the dynamic traffic assignment with South Korea's expressway network and dynamic O/D data by comparing results with observed link traffic volumes. This study used dynamic O/D data between each toll booth, which can be accurately obtained from the highway Toll Collection System. Then, as an example of its application, exclusive bus-lane policies were analyzed with the dynamic traffic assignment model while considering hourly variations.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.30-44
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• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.534-540
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• 2015

In this paper we propose an analytical model for jitter, wherein we implement the interrupted Poisson process (IPP) for incoming traffic. First, we obtain an analytical model for the jitter on one node with respect to the phase probabilities, traffic load, and tagged traffic share in the aggregate traffic flow. Then, we analyze N-node cases, and propose a model for end-to-end jitter. Our analysis leads to some fast-to-compute approximations that can be used for future network design or admission control. Finally, we validate our analytical results by comparing them with previous results for limit cases, as well as with event-driven simulations. We propose the use of our results as guidelines for jitter evaluation of real IP traffic.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.185-203
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• 1995

The purpose of this paper is to develop a microscopic traffic simulation model which is able to both analyze and the evaluate signlaized urban network and to verify its usefulness in comparison with the other model which has alfeady been released. This simulation model adopts the General Motor's 5th model for car-following and introduces an unique lanechanging rule using acceptable gap. It analyzes single and dual-ring signal phases and generates detector information . So it could be applied to dynamic route guidance systems as wel as real time signal control systems. The results derived from Netsim and the observed data from the real network have been used to test the validit of the proposed model. The result of the test has shown that there are no significant differences between the NETSIM model and the proposed model in estimating travel speed and stopped delay. In optimum offset estimatin , it has shown the same results with NETSIM. the measure of effectiveness , however, derived from this model is slightly better than that of the real network situation. This may be due to the fact that the proposed model does not take into account side frictions from interferences and obstacles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1392-1403
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• 2015

The rapid development of both communication traffic and increasing optical network sizes has increased energy consumption. Traditional algorithms and strategies don't apply to controlling the expanded network. Immunization algorithms originated from the complex system theory are feasible for large-scale systems based on a scale-free network model. This paper proposes the immunization strategy for complex systems which includes random and targeted immunizations to solve energy consumption issues and uses traffic to judge the energy savings from the node immunization. The simulation results verify the effectiveness of the proposed strategy. Furthermore, this paper provides a possibility for saving energy with optical transmission networks.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1055-1064
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• 2003

In many automated systems, such as manufacturing systems and process plants, a fieldbus is a very important component for the exchange of various and sometimes crucial information. Some of the information has a tendency to rapidly lose its value as time elapses after its creation. Such information or data is called real-time data that includes sensor values and control commands. In order to deliver these data in time, the fieldbus network should be tailored to have short delay with respect to the individual time limit of various data. Fine-tuning the network for a given traffic requires the knowledge on the relationship between the protocol parameters such as timer values and the performance measure such as network delay. This paper presents a mathematical performance model to calculate communication delays of the Profibus-FMS network when the timer value and the traffic characteristics are given.

• Proceedings of the IEEK Conference
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• summer
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• pp.269-273
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• 2004

This paper presents a comparative performance analysis of a network accelerator model based on M/M/l queuing system. It assumes the Poisson distribution as its input traffic load. The decoding delay is employed as a performance analysis measure. Simulation results based on the proposed model show only $15\%$ differences with respect to actual measurements on field traffic for BCM5820 accelerator device. The performance analysis model provides with reasonable hardware structure of network servers, and can be used to span design spaces statistically.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.187-188
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• 2009

On this study, the artificial neural network, one of the nonlinear forecasting methods, is compared with ARIMA model through performing a forecast of container traffic. The existing studies have been used the rule of thumb in topology design for network which had a great effect on forecasting performance of the artificial neural network. However, this study applied the genetic algorithm, known as the effectively optimal algorithm in the huge and complex sample space, as the alternative.