• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.103-112
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• 2010

A study on network traffic analysis and modeling has been exclusively done due to its importance. However, conventional studies on network traffic analysis and modeling only focus on transmitting simple packet stream or traffic features of specific application, such as HTTP. In this paper, we propose a network traffic generator, which reflects the characteristics of multimedia data. To analyze the traffics of online game, which is one of the most popular multimedia contents, we modeled the distribution according to the time between packets and packet size random variable and designed the traffic generator which has the model for input. We generated the traffics of L4D(Left4Dead), WoW(World of Warcraft) with proposed network traffic generator and we found that the generated traffics have similar distributions with real data.

• The Journal of Bigdata
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• v.2 no.2
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• pp.1-7
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• 2017

Intelligent transportation system (ITS) has been introduced to maximize the efficiency of operation and utilization of the urban traffic facilities and promote the safety and convenience of the users. With the expansion of ITS, various traffic big data such as road traffic situation, traffic volume, public transportation operation status, management situation, and public traffic use status have been increased exponentially. In this paper, we derive structural characteristics of urban traffic according to the vehicle flow by using big data network analysis. DSRC (Dedicated Short Range Communications) data is used to construct the traffic network. The results can help to understand the complex urban traffic characteristics more easily and provide basic research data for urban transportation plan such as road congestion resolution plan, road expansion plan, and bus line/interval plan in a city.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.8
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• pp.335-342
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• 2013

Nowadays, the traffic type and behavior are extremely diverse due to the growth of network speed and the appearance of various services on Internet. For efficient network operation and management, the importance of application-level traffic identification is more and more increasing in the area of traffic analysis. In recent years traffic identification methodology using statistical features of traffic flow has been broadly studied. However, there are several problems to be considered in the identification methodology base on statistical features of flow to improve the analysis accuracy. In this paper, we recognize these problems by analyzing the ground-truth traffic and propose the solution of these problems. The four problems considered in this paper are the distance measurement of features, the selection of the representative value of features, the abnormal behavior of TCP sessions, and the weight assignment to the feature. The proposed solutions were verified by showing the performance improvement through experiments in campus network.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.826-836
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• 2016

Increase of hypertext transfer protocol (HTTP)-based video popularity causes that broadband and Internet service providers' links transmit mainly multimedia content. Network planning, traffic engineering or congestion control requires understanding of the statistical properties of network traffic; therefore, it is desirable to investigate the characteristic of traffic traces generated, among others, by systems which employ adaptive bit-rate streaming. In our work, we investigate traffic originating from 120 client-server pairs, situated in an emulated laboratory environment, and multiplexed onto a single network link. We show that the structure of the traffic is distinct from the structure generated by first and second generation of HTTP video systems, and furthermore, not similar to the structure of general Internet traffic. The obtained traffic exhibits negative correlations, anti-persistence, and its distribution function is skewed to the right. Furthermore, we show that the traffic generated by clients employing the same or similar play-out strategies is positively correlated and synchronised (clustered), whereas traffic originated from different play-out strategies shows negative or no correlations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.541-550
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• 2015

The importance of efficient enterprise network management has been emphasized continuously because of the rapid utilization of Internet in a limited resource environment. For the efficient network management, the management policy that reflects the characteristics of a specific network extracted from long-term traffic analysis is essential. However, the long-term traffic data could not be handled in the past and there was only simple analysis with the shot-term traffic data. However, as the big data analytics platforms are developed, the long-term traffic data can be analyzed easily. Recently, enterprise network resource efficiency through the long-term traffic analysis is required. In this paper, we propose the methods of collecting, storing and managing the long-term enterprise traffic data. We define several classification categories, and propose a novel network resource efficiency through the multidirectional statistical analysis of classified long-term traffic. The proposed method adopted to the campus network for the evaluation. The analysis results shows that, for the efficient enterprise network management, the QoS policy must be adopted in different rules that is tuned by time, space, and the purpose.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.149-157
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• 2016

This paper presents the traffic speed limit of heavy vehicles at each wind velocity region, which is based on their accident risk analysis under cross-wind. The variables for the accident risk analysis are overall height, overall length, intake weight, and friction coefficient of the road surface. It was confirmed from analysis results that the risk of overturning increased with higher overall height and length, and the risk of sliding decreased with higher intake weight. The risk of sliding was largest at the friction coefficient of 0.1, and the risk of overturning was lagest at friction coefficient more than 0.25. Finally, traffic speed limit was proposed by using the accident risk analysis.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.81-95
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• 2001

This paper models and evaluates the AAL multiplexer to analyze AAL protocol in ATM networks. We consider an AAL multiplexer in which a single periodically determinsitic CBR traffic stream and several variable size bursty background traffic streams are multiplexed and one ATM cell stream goes out. We model the AAL multiplexer as a B/sup X/ + D/D/1/K queue and analyze this queueing system. We represent various performance measures such as loss probability and waiting time in the basis of cell and packet.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.101-116
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• 1996

Increased attention has been paid in recent years to the need of traffic management for alleviating urban traffic congestion. This paper presents a discrete event modeling and simulation framework for analyzing the traffic flow. Traffic simulation models can be classified as being either microscopic and macroscopic models. The discrete event modeling and simulation technique can be basically employed to describe the macroscopic traffic simulation model. To do this, we have employed the System Entity Structure/Model Base (SES/MB) framework which integrates the dynamic-based formalism of simulation with the symbolic formalism of AI. The SES/MB framework supports to hierarchical, modular discrete event modeling and simulation environment. We also adopt the Symbolic DEVS (Discrete Event System Specification) to developed the automated analysis methodology for generating optimal signal light policy. Several simulation tests will demonstrates the techniques.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.404-410
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• 1999

A scheme of more exact overflow probability analysis is proposed for traffic regulated by dual leaky bucket. To each regulated traffic stream is allocated bandwidth and buffer independent of other traffic stream and overflow occurs when total bandwidth or buffer allocated to each traffic exceed link capacity or physical buffer size. Ratio of buffer and bandwidth allocated to each traffic stream is assumed to be constant, and this ratio is larger than the ratio of physical buffer and bandwidth due to buffer sharing effect. Numerical experiments show that this sharing effect have significant influence on overflow probability and effective bandwidth.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.307-313
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• 2011

In this paper, we compare performance of three models. The Holt-Winters, FARIMA and ARGARCH models, are used in predicting internet traffic data for analysis of traffic characteristics. We first introduce the time series models and apply them to real traffic data to forecast. Finally, we examine which model is the most suitable for explaining the long memory, the characteristics of the traffic material, and compare the respective prediction performance of the models.