• Title/Summary/Keyword: traffic assignment

Search Result 254, Processing Time 0.029 seconds

Edge Router Selection and Traffic Engineering in LISP-Capable Networks

  • Li, Ke;Wang, Sheng;Wang, Xiong
    • Journal of Communications and Networks
    • /
    • v.13 no.6
    • /
    • pp.612-620
    • /
    • 2011
  • Recently, one of the problems with the Internet is the issue of scalability. To this end, locator/identifier separation protocol (LISP), which separates end-system identifiers and routing locators, has been proposed as a solution. In the LISP deployed network, the ingress and egress nodes of inter-AS traffic is determined by edge router selection (ERS) and endpoint identifier-routing locator mapping assignment (ERMA). In this paper, joint optimizations of ERS and ERMA for stub networks with and without predetermined link weights are studied and the mixed integer linear programming (MILP) formulations for the problems are given. To make the problem with optimizable link weights tractable, a revised local search algorithm is also proposed. Simulation results show that joint optimization of ERS and ERMA enables better network performance.

A Sensitivity Analysis of Traffic Assignment (교통배분의 민감도 분석에 관한 연구)

  • 장덕오
    • Journal of Korean Society of Transportation
    • /
    • v.11 no.3
    • /
    • pp.31-48
    • /
    • 1993
  • 본 연구에서는 다른 기종점 통행표(Trip Matrices)들을 같은 교통망(Network)에 배정하였을 때 교통분배 결과의 차이점들을 분석하고 교통분배의 민감도를 비교하였다. 전통적인 4단계 교통수요 추정에 의해서 산출된 교통배분을 비교의 기본자료로 이용했다. 또한 본 연구에서는 교통배분의 결과를 평가하기 위해 주로 사용하는 측정효과들과 교통배분의 기법들(Traffic Assignment Techniques)의 민감도도 연구조사하였다. 본 연구를 통하여 총교통량(Total Trips)과 통행길이빈도(Trip Length Frequency)제약에 의해 임의로 선출된 기종점 통행표를 이용한 교통배분의 결과는 전통적인 4단계 교통수요 측정에 의해 산출된 교통배분 및 조사교통량(Counted Traffic Volumes)에 매우 유사한 결과가 나왔다. 결론적으로 죤별 통행발생량에서의 오차는 교통배분의 본성적인 집계특성(Aggregative Nature)에 의하여 그 심각성이 감소되는 경향이 있다. 이것은 즉 앞단계(Trip Generation and Distribution Phases)에서 전통적으로 요구되어지는 정밀도가 없어도 적절한 교통배분기법을 사용함으로써 좋은 결과를 산출할 수 있다는 것을 암시한다.

  • PDF

Label Assignment Schemes for MPLS Traffic Engineering (MPLS 트래픽 엔지니어링을 위한 레이블 할당 방법)

  • 이영석;이영석;옥도민;최양희;전병천
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.25 no.8A
    • /
    • pp.1169-1176
    • /
    • 2000
  • In this paper, label assignment schemes considering the IP flow model for the efficient MPLS traffic engineering are proposed and evaluated. Based on the IP flow model, the IP flows are classified into transient flows and base flows. Base flows, which last for a long time, transmit data in high bit rate, and be composed of many packets, have good implications for the MPLS traffic engineering, because they usually cause network congestion. To make use of base flows for the MPLS traffic engineering, we propose two base flow classifiers and label assignment schemes where transient flows are allocated to the default LSPs and base flows to explicit LSPs. Proposed schemes are based on the traffic-driven label triggering method combined with a routing tabel. The first base flow classifier uses both flow size in packet counts and routing entries, and the other one, extending the dynamic X/Y flow classifier, is based on a cut-through ratio. Proposed schemes are shown to minimize the number of labels, not degrading the total cut-through ratio.

  • PDF

A Volume-Delay Function Parameter Estimation and Validation for Traffic Assignment (도로 통행지체함수의 파라미터 추정 및 검증)

  • Lim, Yong-Taek;Kang, Min-Gu;Choo, Sang-Ho;Lee, Sang-Min
    • Journal of Korean Society of Transportation
    • /
    • v.26 no.3
    • /
    • pp.17-29
    • /
    • 2008
  • A volume-delay function(VDF) has been used to describe the relation between traffic volumes and delay experienced by travelers on the roads traveling from origin to destination, which has been usually adopted in traffic assignment. For the purpose of more precise description of traffic pattern, we have to estimate the parameters of VDF in advance. This paper presents a methodology for estimating the parameters, which combined with golden section method. By using the method we have estimated the parameters with real data based on KTDB(2006), and validated them. Compared to the existing values of the parameters, newly estimated values are found to be closer to real world.

Practical Interpretation and Source of Error in Traffic Assignment Based on Korea Transport Database(KTDB) (KTDB 기반 노선배정의 예측오차 원인과 분석결과 해석)

  • KIM, Ikki
    • Journal of Korean Society of Transportation
    • /
    • v.34 no.5
    • /
    • pp.476-488
    • /
    • 2016
  • This study reviewed factors and causes that affect on reliability and accuracy of transportation demand forecasting. In general, the causes of forecasting errors come from variety and irregularity of trip behaviors, data limitation, data aggregation and model simplification. Theoretical understanding about the inevitable errors will be helpful for reasonable decision making for practical transportation policies. The study especially focused on traffic assignment with the KTDB data, and described the factors and causes of errors by classifying six categories such as (1) errors in input data, (2) errors due to spacial aggregation and representation method of network, (3) errors from representing values for variations of traffic patterns, (4) errors from simplification of traffic flow model, and (5) errors from aggregation of route choice behavior.

Solution Methods for OD Trip Estimation in Stochastic Assignment (확률적 통행배정하에서 기종점 통행량추정 모형의 개발)

  • Im, Yong-Taek
    • Journal of Korean Society of Transportation
    • /
    • v.24 no.4 s.90
    • /
    • pp.149-159
    • /
    • 2006
  • Traditional trip tables are estimated through large-scale surveys such as household survey, roadside interviews, and license Plate matching. These methods are, however, expensive and time consuming. This paper presents two origin-destination (OD) trip matrix estimation methods from link traffic counts in stochastic assignment, which contains perceived errors of drivers for alternatives. The methods are formulated based on the relation between link flows and OD demands in logit formula. The first method can be expressed to minimize the difference between observed link flows and estimated flows, derived from traffic assignment and be solved by gradient method. The second method can be formulated based on dynamic process, which nay describe the daily movement patterns of drivers and be solved by a recursive equation. A numerical example is used for assessing the methods, and shows the performances and properties of the models.