• Title/Summary/Keyword: traffic data

Search Result 4,766, Processing Time 0.041 seconds

Implementation of Wireless Network simulator considering a User's Call Characteristics (사용자 통화 특성을 고려한 무선 네트워크 시뮬레이터 구현)

  • Yoon, Young Hyun
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.5 no.3
    • /
    • pp.107-115
    • /
    • 2009
  • Traditionally, simulation method is used to test and evaluate the performance of communication protocol or functional elements for mobile communication service. In this paper, wireless network simulator is implemented using the C++ object-oriented programming language. This simulator can simulate wireless data services, like as ad-hoc networks, by considering the user's mobility. In this paper, the simulator includes network traffic model to reflect wireless data service and traffic source model to represent a user's mobility similar to real service environment and traffic characteristics can be reflected on the simulation, and also more accurate simulation results can be got through that. In addition, by using object-oriented techniques, new service feature or environment can be easily added or changed so that the developed mobile communication simulator can reflect the real service environment all the time. This simulator can be used in adjusting the characteristics of wireless data hosts following the mobility of the user, and also can be used in building new wireless ad-hoc network routing protocols.

Regional Traffic Accident Model of Elderly Drivers based on Urban Decline Index (도시쇠퇴 지표를 적용한 지역별 고령운전자 교통사고 영향 분석)

  • Park, Na Young;Park, Byung Ho
    • Journal of the Korean Society of Safety
    • /
    • v.32 no.6
    • /
    • pp.137-142
    • /
    • 2017
  • This study deals with the relation between traffic accident and urban decline. The purpose of this study is to develop the regional accident models of elderly drivers. In order to develop the count data models, 2009-2015 traffic accident data from TAAS(traffic accident analysis system) and urban decline data from urban regeneration information system are collected. The main results are as follows. First, the null hypothesis that there is no difference in the accident number between elderly and non-elderly drivers is rejected. Second, 8 accident models which are all statistically significant have been developed. Finally, common variables between elderly and non-elderly are ratio of elderly people, elderly person living alone/1,000 persons and wholesale/retail employments/1,000 persons. This study could be expected to give many implications to making regional accident reduction policy.

Self-Similarity Characteristic in Data traffic (데이터 트래픽 Self-Similar 특성에 관한 연구)

  • 장우현;오행석
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2000.10a
    • /
    • pp.272-277
    • /
    • 2000
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction, However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially hem the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

  • PDF

Mobile Communications Data traffic using Self-Similarity Characteristic (Self-Similar 특성을 이용한 이동전화 데이터 트래픽 특성)

  • 이동철;양성현;김기문
    • Journal of the Korea Computer Industry Society
    • /
    • v.3 no.7
    • /
    • pp.915-920
    • /
    • 2002
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish yon that it makes out about the characteristics of actual data traffic more easily.

  • PDF

Self-Similarity Characteristic in Data traffic (Self-Similar특성을 이용한 데이터 트래픽 특성에 관한 연구)

  • 이동철;김기문;김동일
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2001.05a
    • /
    • pp.173-178
    • /
    • 2001
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

  • PDF

A Low Complexity PTS Technique using Threshold for PAPR Reduction in OFDM Systems

  • Lim, Dai Hwan;Rhee, Byung Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.6 no.9
    • /
    • pp.2191-2201
    • /
    • 2012
  • 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.

Performance Comparison between Expressnet and FDDI for intergrated Voice and Data Traffic (음성과 데이터의 통합트래픽에 대한 Expressnet과 FDDI의 성능비교)

  • Joo, Gi-Ho
    • The Journal of Natural Sciences
    • /
    • v.8 no.2
    • /
    • pp.93-99
    • /
    • 1996
  • In this study, we compare performance of priority schemes of FDDI and Expressnet for integrated voice and data traffic through simulation. The voice capacity of FDDI is higher than that of Expressnet for all cases considered. When compared to Expressnet, FDDI achieves a higher data throughput for file transfer traffic but it incurs a longer delay for interactive traffic.

  • PDF

Self-Similarity Characteristic in Data traffic (Self-Similar특성을 이용한 데이터 트래픽 특성에 관한 연구)

  • 이동철;김기문;김동일
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2001.10a
    • /
    • pp.454-459
    • /
    • 2001
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

  • PDF

Self-Similarity Characteristic in Mobile Communications Data traffic (이동전화 데이터 트래픽에서의 Self-Similar 특성)

  • 이동철;정인명;김기문;김동일
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2001.10a
    • /
    • pp.468-471
    • /
    • 2001
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

  • PDF

Noise Simulation of Road Traffic in Urban Area Using LiDAR Data for U-City Construction (U-City 건설을 위한 LiDAR 자료를 이용한 도심지 도로교통소음 영향의 시뮬레이션 분석)

  • Cho, Jae-Myoung;Lee, Dong-Ha;Yun, Hong-Sic;Lee, Seung-Huhn
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.25 no.3
    • /
    • pp.199-205
    • /
    • 2007
  • In this study, we have intended to precisely analyze the aspect of propagation and the extent of damage due to the traffic noise as hon as a main source of noise in urban area. The propagation of traffic noise has a strong relationship between distance and shape of surface. Thus, it is necessary to consider the distribution of buildings for estimating effects of noise in urban area because noise propagations will be affected by buildings. For this, we developed the DEM and DBM using the airborne LiDAR data in the study area and compared with results from the noise simulations using the each model. The extent of damage occurred by the traffic noise above 60 dB(A) from the case of DEM were shown at the 60% of a whole study area, whereas the extent from other case of DBM were shown at the 30% of a whole study area. Also, the extent of the noise levels between 45 dB(A) and 50 dB(A) will be generally recognized as calm environment was increased(the 0% to the 43%) in the case which simulated with building informations. These results indicated that the shape informations of buildings like a DBM is a essential source to simulate the propagation of traffic noise in urban area especially. With results in this study, the effect of traffic noise at a specific area will be easily and precisely estimated if we have the LiDAR data and a traffic census for Korea. Furthermore specific area's traffic noise simulation could be possible using only road traffic information once we have DBM data from LiDAR surveying. This also could be applied as a base data for noise pollution petitioning, traffic planning, construction, etc. in huge city planning projects like a U-City.