• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.33-43
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• 2004

In this paper, a traffic trend analysis based SNMP algorithm is proposed for improving the problem of existing traffic analysis using SNMP. The existing traffic analysis method has a vulnerability that is taken much time In analyzing by using a threshold and not detected a harmful traffic at the point of transition. The method that is proposed in this paper can solve the problems that the existing method had, simultaneously using traffic trend analysis of the day, traffic trend analysis happening in each protocol and MIB object analysis responding to attacks instead of using the threshold. The algorithm proposed in this paper will analyze harmful traffic more quickly and more precisely; hence it can reduce the damage made by traffic flooding attacks. When traffic happens, it can detect the abnormality through the three analysis methods previously mentioned. After that, if abnormal traffic overlaps in at least two of the three methods, we can consider it as harmful traffic. The proposed algorithm will analyze harmful traffic more quickly and more precisely; hence it can reduce the damage made by traffic flooding attacks.

• Proceedings of the IEEK Conference
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• summer
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• pp.171-175
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• 2004

Network management for detail analysis can cause speed decline of application in case of lack band width by traffic increase of the explosive Internet. Because a manager requests MIB value for the desired objects to an agent by management policy, and then the agent responds to the manager. Such processes are repeated, so it can cause increase of network traffic. Specially, repetitious occurrence of sending-receiving information is very inefficient for a same object when a trend analysis of traffic is performed. In this paper, an efficient SNMP is proposed to add new PDUs into the existing SNMP in order to accept time function. Utilizing this PDU, it minimizes unnecessary sending-receiving message and collects information for trend management of network efficiently. This proposed SNMP is tested for compatibility with the existing SNMP and decreases amount of network traffic largely

• Atmosphere
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• v.31 no.2
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• pp.157-170
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• 2021

To investigate the effect of snowfall on the traffic of general roads in Gangwon-do, case analysis was performed in Gangneung, Pyeongchang, and Chuncheon using ASOS (Automated Synoptic Observing System) snowfall data and VDS (Vehicle Detector System) traffic data. First, we analyzed how much the traffic volume and speed decrease in snowfall cases on regional roads compared to non-snow cases, and the characteristics of monthly reduction due to snowfall were investigated. In addition, Pearson correlation analysis and regression analysis were performed to quantitatively grasp the effect of snowfall on traffic volume and speed, and sensitivity tests for snowfall intensity and cumulative snowfall were performed. The results showed that the amount of snowfall caused decrease both in the traffic volume and speed from usual (non-snowfall) condition. However, the trend was different by region: The decrease rate in traffic volume was in the order of Gangneung (17~22%), Chuncheon (14~17%), and Pyeongchang (11~14%). The decrease rate in traffic speed was in the order of Chuncheon (9~10%), Gangneung (8~9%), Pyeongchang (5~6%). No significant results were found in the monthly decrease rate analysis. In all regions, traffic volume and speed showed a negative correlation with snowfall. It was confirmed that the greater the amount of traffic entering the road, the greater the slope of the trend line indicating the change in snowfall due to the traffic volume. As a result of the sensitivity test for snowfall intensity and cumulative snowfall, the snowfall information at intervals of 6-hours was the most significant.

• Journal of IKEEE
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• v.13 no.2
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• pp.140-149
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• 2009

Traffic anomaly detection is one of important technology that should be considered in network security and administration. In this paper, we propose an abnormal traffic detection mechanism that includes traffic monitoring and traffic analysis. We develop analytical passive monitoring system called WISE-Mon which can inspect traffic behavior. We establish a criterion by analyzing the characteristics of a traffic training set. To detect abnormal traffic, we derive a hyperplane by using Fisher linear discriminant and chi-square distribution as well as the analyzed characteristics of traffic. Our mechanism can support reliable results for traffic anomaly detection and is compatible to real-time detection. In addition, since the trend of traffic can be changed as time passes, the hyperplane has to be updated periodically to reflect the changes. Accordingly, we consider the self-learning algorithm which reflects the trend of the traffic and so enables to increase the pliability of detection probability. Numerical results are presented to validate the accuracy of proposed mechanism. It shows that the proposed mechanism is reliable and relevant for traffic anomaly detection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.361-368
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• 2003

An SNMP manager requests a value in MIB of a designated object to an agent by management policy defined in the SNMP, and then the agent responds to this manager. So, it causes a lot of networks traffic between them, Specially, repetitious occurrence of sending-receiving information related to the same object is very inefficient when the trend analysis of traffic is performed. In this paper, an efficient SNMP is proposed to add new PDUs to the existing SNMP in order to accept time function. Utilizing this PDU, it minimizes unnecessary sending-receiving information and collects information on trend management appropriately. The implemented SNMP is tested for compatibility with the existing SNMP and decreases the amount of network traffic greatly.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.323-333
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• 2012

Network traffic demand is increasing explosively because of various smart equipment and services on smart era. It causes of traffic overload for wireless and wired network. Network management system is very important to control the explosion of data traffic. It uses SNMP to communicate with various network resources for management functions and creates lots of management traffic. Those are can be serious traffic congestion on a network. I propose an improving function of SNMP to minimize unnecessary traffics between manager and agent for collecting the Trend Analysis Information which is mainly used to monitor and accumulate for a specific time period in this paper. The results of test show it has compatibility with the existing SNMP and greatly decreases the amount of network traffic and response time.

• Journal of the Korean Society of Safety
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• v.29 no.2
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• pp.76-81
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• 2014

Railroad traffic accident consists of train accident, level-crossing accident, traffic death and injury accident caused by train or vehicle, and it is showing a continuous downward trend over a long period of time. As a result of the frequency comparison of train accidents and level-crossing accidents using the railway accident statistics data of Railway Industry Information Center, the share of train accident is over 90% in the 1990s and 80% in the 2000s more than the one of level-crossing accidents. In this study, we investigated time series characteristic and short-term prediction of railroad crossing, as well as seasonal characteristic. The analysis data has been accumulated over the past 20 years by using the frequency data of level-crossing accident, and was used as a frequency data per month and year. As a result of the analysis, the frequency of accident has the characteristics of the seasonal occurrence, and it doesn't show the significant decreasing trend in a short-term.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.65-78
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• 2017

Even though cars have a good effect on modern society, traffic accidents do not. There are traffic laws that define the regulations and aim to reduce accidents from happening; nevertheless, it is hard to determine all accident causes such as road and traffic conditions, and human related factors. If a traffic accident occurs, the traffic law classifies it as 'Negligence of Safe Driving' for cases that are not defined by specific regulations. Meanwhile, as Korea is already growing rapidly elderly population with more than 65 years, so are the number of traffic accidents caused by this group. Therefore, we studied predictive and comparative analysis of the number of traffic accidents caused by 'Negligence of Safe Driving' by dividing it into two groups : All-ages and Elderly. In this paper, we used empirical monthly data from 2007 to 2015 collected by TAAS (Traffic Accident Analysis System), identified the most suitable ARIMA forecasting model by using the four steps of the Box-Jenkins method : Identification, Estimation, Diagnostics, Forecasting. The results of this study indicate that ARIMA $(1, 1, 0)(0, 1, 1)_{12}$ is the most suitable forecasting model in the group of All-ages; and ARIMA $(0, 1, 1)(0, 1, 1)_{12}$ is the most suitable in the group of Elderly. Then, with this fitted model, we forecasted the number of traffic accidents for 2 years of both groups. There is no large fluctuation in the group of All-ages, but the group of Elderly shows a gradual increase trend. Finally, we compared two groups in terms of the forecast, suggested a countermeasure plan to reduce traffic accidents for both groups.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.7-15
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• 2011

Emerged in early 1990s, so called 'Quick service' industry that provides faster delivery of small parcels than regular mail service accelerated use of motorcycles. As the economic grows, use of large bicycles (more than 250CC displacement) for leisure purpose has also rapidly increased. Traffic crash data clearly shows the increasing trend in motorcycle crashes. The ratio of motorcycle involved crashes out of total has increased from 5.7% in 2005 to 8.3% in 2008, and similar trend can be found in fatalities ratio as well. In this study, we assess the level of risk when motorcycles operate on motorways by analyzing traffic rule violation ratio, lane change behaviour, driving speed behaviors of motorcycles in Uninterrupted Traffic Flow Facilities and using PC-CRASH simulation we also calculate car shock impulses occurred when an accident happens. Analysis result shows that the motorcycle is different from the car in terms of lane change timing and average speed, and also shows motorcycle drivers tends to conduct more improper driving behavior particularly when traffic is congested. The results from this study could be usefully applied when the law enforcement agent decides whether bicycles shall be allowed to use motorways. The result could be also utilized as fundamental information for further study of bicycles' driving behavior.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1266-1276
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• 2003

Multimedia information containing voice and image is transmitted on Internet, which is ten times or hundred times larger than ordinary information. Analysis types for network management in this environment consist of a real time analysis, a basic analysis and an intensive analysis. The intensive analysis is useful for gathering the trend information of specific objects periodically for certain period in order to monitor network status. When SNMP is applied to collect the trend information of intensive analysis, it brings on the increase of network load, the delay of response time and the decrease of data collection accuracy since an agent responds to manager's every polling. In this paper, an efficient SNMP is proposed and implemented to add time variables in the existing SNMP PDU. It minimizes unnecessary traffic in the intensive analysis between manager and agent, and collects trend information more accurately. The results of experiments show that it has compatibility with the existing SNMP, decreases the amount of network traffic greatly and increases the accuracy of data collection.