• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.331-335
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• 1999

LAN, WAN 및 VBR 트래픽 특성에 관한 최근의 실험적 연구들은 기존의 Poisson 가정에 의한 모델들이 네트워크 트래픽의 장기간 의존성 및 self-similar 특성들을 과소평가 함으로써, 실제 트래픽의 특성을 제대로 나타낼 수 없다는 것을 지적해 왔다. 본 본문에서는 실시간 운영중인 Ethernet 트래픽을 측정하여, 통계학적인 접근법들을 통해 이러한 self-similar 특성들에 대해 평가하였다. 그리고 exactly self-similar 모델링인 Pareto-like ON/OFF 소스 모델링에 의한 트래픽과 기존의 Poisson 모델링을 비교 분석함으로써, self-similar 트래픽이 실제의 Ethernet 트래픽 특성을 잘 반영한다는 것을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5A
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• pp.294-304
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• 2003

For an efficient software download in cellular CDMA systems, session admission control based on area (SACA) is presented. In the SACA scheme, the base station only allows mobile terminal to start session when the mobile locates near the base station of a cell. A mobile that is located near cell center can request software download session, but the mobile that is far away from the center can request session only after arriving near the cell center. Session duration time follows exponential and Pareto distribution. Performance is analyzed in terms of handoff rate, mean channel holding time, session blocking probability and handoff forced termination probability. As analysis results, handoff rate between cells in the proposed scheme is reduced to 30 ~ 250 % compared to conventional scheme, according to traffic characteristics such as terminal speed, session duration time and the size of the allowable zone area in a cell for the start of the session. And new session blocking probability slightly decreases to 5 ~ 20 %, but handoff session forced termination probability drastically decreases to 35 ~ 220 %.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.