The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
네트워크 단층 촬영에서 현재까지의 대부분의 작업은 링크 손실률과 지연 분포를 추론하기 위해 프로브 패킷 수준 상관 관계를 활용하는 데 기반을 두고 있습니다. 일부 다른 작업은 상관되지 않은 엔드투엔드 측정과 링크 사전 혼잡 가능성을 사용하여 혼잡한 링크를 식별하는 데 중점을 둡니다. 그들의 작업에서 사전 확률은 여러 측정 스냅샷을 사용한 행렬 역전으로 식별되며 혼잡한 링크를 찾는 알고리즘은 경험적이며 최적이 아닙니다. 이 편지에서 우리는 측정 스냅샷의 명시적 기능인 계산적으로 간단한 사전 확률에 대한 새로운 추정기를 제시합니다. 이러한 사전 확률을 사용하여 혼잡한 링크 세트를 식별하는 것은 확률 최대화 문제에 대한 솔루션을 찾는 것과 동일합니다. 우리는 이 문제에 대한 해결책을 찾기 위해 FBA라는 빠른 상향식 접근 방식을 제안합니다. FBA는 상향식으로 솔루션을 단계별로 최적화합니다. 우리는 FBA에 의한 솔루션이 최적임을 증명합니다.
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Haibo SU, Shijun LIN, Yong LI, Li SU, Depeng JIN, Lieguang ZENG, "A Fast Bottom-Up Approach to Identify the Congested Network Links" in IEICE TRANSACTIONS on Communications,
vol. E93-B, no. 3, pp. 741-744, March 2010, doi: 10.1587/transcom.E93.B.741.
Abstract: In network tomography, most work to date is based on exploiting probe packet level correlations to infer the link loss rates and delay distributions. Some other work focuses on identifying the congested links using uncorrelated end-to-end measurements and link prior probability of being congested. In their work, the prior probabilities are identified by the matrix inversion with a number of measurement snapshots, and the algorithm to find the congested links is heuristic and not optimal. In this letter, we present a new estimator for the prior probabilities that is computationally simple, being an explicit function of the measurement snapshots. With these prior probabilities, the identification of the congested link set is equivalent to finding the solution for a probability maximization problem. We propose a fast bottom-up approach named FBA to find the solution for this problem. The FBA optimizes the solution step by step from the bottom up. We prove that the solution by the FBA is optimal.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E93.B.741/_p
부
@ARTICLE{e93-b_3_741,
author={Haibo SU, Shijun LIN, Yong LI, Li SU, Depeng JIN, Lieguang ZENG, },
journal={IEICE TRANSACTIONS on Communications},
title={A Fast Bottom-Up Approach to Identify the Congested Network Links},
year={2010},
volume={E93-B},
number={3},
pages={741-744},
abstract={In network tomography, most work to date is based on exploiting probe packet level correlations to infer the link loss rates and delay distributions. Some other work focuses on identifying the congested links using uncorrelated end-to-end measurements and link prior probability of being congested. In their work, the prior probabilities are identified by the matrix inversion with a number of measurement snapshots, and the algorithm to find the congested links is heuristic and not optimal. In this letter, we present a new estimator for the prior probabilities that is computationally simple, being an explicit function of the measurement snapshots. With these prior probabilities, the identification of the congested link set is equivalent to finding the solution for a probability maximization problem. We propose a fast bottom-up approach named FBA to find the solution for this problem. The FBA optimizes the solution step by step from the bottom up. We prove that the solution by the FBA is optimal.},
keywords={},
doi={10.1587/transcom.E93.B.741},
ISSN={1745-1345},
month={March},}
부
TY - JOUR
TI - A Fast Bottom-Up Approach to Identify the Congested Network Links
T2 - IEICE TRANSACTIONS on Communications
SP - 741
EP - 744
AU - Haibo SU
AU - Shijun LIN
AU - Yong LI
AU - Li SU
AU - Depeng JIN
AU - Lieguang ZENG
PY - 2010
DO - 10.1587/transcom.E93.B.741
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E93-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2010
AB - In network tomography, most work to date is based on exploiting probe packet level correlations to infer the link loss rates and delay distributions. Some other work focuses on identifying the congested links using uncorrelated end-to-end measurements and link prior probability of being congested. In their work, the prior probabilities are identified by the matrix inversion with a number of measurement snapshots, and the algorithm to find the congested links is heuristic and not optimal. In this letter, we present a new estimator for the prior probabilities that is computationally simple, being an explicit function of the measurement snapshots. With these prior probabilities, the identification of the congested link set is equivalent to finding the solution for a probability maximization problem. We propose a fast bottom-up approach named FBA to find the solution for this problem. The FBA optimizes the solution step by step from the bottom up. We prove that the solution by the FBA is optimal.
ER -