• Journal of Korean Society of Transportation
• /
• v.33 no.1
• /
• pp.14-28
• /
• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• Journal of Korea Multimedia Society
• /
• v.7 no.3
• /
• pp.399-407
• /
• 2004

As the number of IP-users are increasing, it is getting so important for service providers to check the state of the current Internet and their service quality by measuring the traffic quality. We describe a general concept of measurement architecture and internet QoS (Quality of Service) parameters, and we review measurement tools. To meet these requirements, we design and implement the Internet traffic management system.

• ETRI Journal
• /
• v.35 no.2
• /
• pp.253-258
• /
• 2013

We propose and demonstrate an efficient power-saving optical network unit (ONU) based on upstream traffic monitoring for 10-Gb/s wavelength division multiplexed passive optical networks (WDM-PONs). The power-saving mode controller uses a ${\mu}$-processor and traffic monitoring modules followed by the proposed power-saving processes to operate the sleep mode ONU. The power consumption of the ONU is effectively reduced from 19.3 W to 6.4 W when no traffic from the users is detected. In addition, we design a power-saving mechanism based on a cyclic sleep mode operation to allow a connectivity check between the optical line terminal and ONU. Our calculation results show that the WDM-PON ONU reduces the power consumption by around 60% using the proposed mechanism.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.1
• /
• pp.113-120
• /
• 2010

In case the traffic accident occurs, skid mark is very important factor to calculate the car speed. Especially, for the purpose of objective and scientific inspection, traffic accidents should be appraised and inspected by righteous material evidences, computer simulation, and studies such as automobile engineering, traveling and collision accident dynamics, road and traffic engineering. In this paper, it displays the results of studying cases with the reasons of traffic accidents by analyzing and studying automobile kinetics, real traffic accidents and the results of in scientific and objective ways. After computer simulation result that it is proved that compared with unpacked road condition and packed road condition. unpacked road condition is shorter than packed road condition.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.86-88
• /
• 2004

As the rapid incensement of the number of internet users has occurred recently, many multimedia application services have been emerging. To improve quality of service, traffic can be suggested to be classified with priority in EPON(Ethernet Passive Optical Network), which is supporting the multimedia application services. In this paper, multimedia application services treat bandwidth classifying device in serving both delay sensitive traffic for real-time audio, video and voice data such as VoIP(Voice over Internet Protocol), and nonreal-time traffic such as BE(Best Effort). With looking through existing mechanisms, new mechanism to improve the quality will be suggested. The delay performances and packet losses of traffic achieved by supporting bandwidth allocation of upstream traffic in suggested mechanism will be analyzed with simulation.

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

• Journal of The Institute of Information and Telecommunication Facilities Engineering
• /
• v.9 no.4
• /
• pp.131-140
• /
• 2010

Recently, mobile wireless data traffic has been dramatically increased due to not only the popularization of digital convergence devices including smart phone, Net-book, and Tablet PC, but also the vitalization of wireless Internet related eco-systems such as AppStore. In addition, it is expected that a tremendous increase in mobile data is caused by the release of unlimited mobile data plans (flat-fee). In order to deal with such mobile data traffic explosion, it is necessary that network operators should make efforts to offload wireless data traffic. This paper reviews the condition of mobile wireless data traffic in domestic and international telecommunication industry and looks for various action plans to overcome the difficulty of network operators.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.2
• /
• pp.134-146
• /
• 2009

Traffic classification seeks to assign packet flows to an appropriate quality of service(QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.

• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.57-60
• /
• 2004

Next generation wireless network is evolving toward IP-based network that can various provide multimedia services. A challenge in wireless mobile Internet is support of quality of service over wireless access networks. DiffServ architecture is proposed for evolving wireless mobile Internet. In this paper we propose an algorithm for optimal buffer partitioning which requires the minimal channel capacity to satisfy the QoS requirements of input traffic. We used a partitioned buffer with size B to serve a layered traffic at each DiffServ router. We consider a traffic model with a single source generates traffic having J $(J\geq2)$ quality of service (QoS) classes. QoS in this case is described by loss probability $\varepsilon_j$. for QoS class j. Traffic is admitted or rejected based on the buffer occupancy and its service class. Traffic is generated by heterogeneous Markov-modulated fluid source (MMFS).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.8B
• /
• pp.921-928
• /
• 2011

The increase of Internet users and services has caused the upsurge of data traffic over the network. Nowadays, variety of Internet applications has emerged which generates complicated and diverse data traffic. For the efficient management of Internet traffic, many traffic classification methods have been proposed. But most of the methods focused on the application-level classification, not the function-level classification or state changes of applications. The functional classification of application traffic makes possible the in-detail understanding of application behavior as well as the fine-grained control of applications traffic. In this paper we proposed automata based functional classification method of IM application traffic. We verified the feasibility of the proposed method with function-level control experiment of IM application traffic.