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
효과적인 네트워크 관리를 위해서는 트래픽 측정을 통한 플로우 수준의 성능 관리가 매우 중요합니다. 링크 속도가 급격하게 상승하면서 모든 패킷을 수집하는 것이 어려워지면서 패킷 샘플링은 흐름 통계를 측정하는 확장 가능한 수단으로 주목을 받고 있습니다. 본 논문에서는 먼저 패킷 샘플링을 통해 샘플링된 플로우의 TCP 플로우율을 추정하는 방법을 제안하고, 추정된 플로우율로부터 TCP 플로우 수준에서의 성능 저하를 탐지하는 방법을 개발한다. 유속 추정 방법에서는 샘플링된 패킷의 시퀀스 번호를 사용하므로 샘플링된 플로우의 유속 추정 정확도를 크게 향상시킬 수 있습니다. 분석 모델과 측정 데이터를 모두 사용하여 이 방법이 정확한 추정을 제공한다는 것을 보여줍니다. 또한 샘플링된 흐름의 추정 속도를 관찰하여 TCP 성능 저하를 감지할 수 있음을 보여줍니다. 성능 저하를 탐지하는 방법은 (i) 샘플링된 흐름은 높은 유속을 갖는 경향이 있다는 것과 (ii) 링크가 정체되면 높은 유속의 흐름이 먼저 성능이 저하된다는 두 가지 사실을 기반으로 합니다. 이러한 특성은 샘플링된 플로우가 혼잡에 민감하다는 것을 의미하므로 샘플링된 플로우의 속도를 관찰하여 혼잡에 민감한 플로우의 성능 저하를 감지할 수 있습니다. 또한 측정 데이터를 사용하여 방법의 효율성을 보여줍니다.
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부
Ryoichi KAWAHARA, Tatsuya MORI, Keisuke ISHIBASHI, Noriaki KAMIYAMA, Hideaki YOSHINO, "Packet Sampling TCP Flow Rate Estimation and Performance Degradation Detection Method" in IEICE TRANSACTIONS on Communications,
vol. E91-B, no. 5, pp. 1309-1319, May 2008, doi: 10.1093/ietcom/e91-b.5.1309.
Abstract: Managing the performance at the flow level through traffic measurement is crucial for effective network management. With the rapid rise in link speeds, collecting all packets has become difficult, so packet sampling has been attracting attention as a scalable means of measuring flow statistics. In this paper, we firstly propose a method of estimating TCP flow rates of sampled flows through packet sampling, and then develop a method of detecting performance degradation at the TCP flow level from the estimated flow rates. In the method of estimating flow rates, we use sequence numbers of sampled packets, which make it possible to improve markedly the accuracy of estimating the flow rates of sampled flows. Using both an analytical model and measurement data, we show that this method gives accurate estimations. We also show that, by observing the estimated rates of sampled flows, we can detect TCP performance degradation. The method of detecting performance degradation is based on the following two findings: (i) sampled flows tend to have high flow-rates and (ii) when a link becomes congested, the performance of high-rate flows becomes degraded first. These characteristics indicate that sampled flows are sensitive to congestion, so we can detect performance degradation of flows that are sensitive to congestion by observing the rate of sampled flows. We also show the effectiveness of our method using measurement data.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.5.1309/_p
부
@ARTICLE{e91-b_5_1309,
author={Ryoichi KAWAHARA, Tatsuya MORI, Keisuke ISHIBASHI, Noriaki KAMIYAMA, Hideaki YOSHINO, },
journal={IEICE TRANSACTIONS on Communications},
title={Packet Sampling TCP Flow Rate Estimation and Performance Degradation Detection Method},
year={2008},
volume={E91-B},
number={5},
pages={1309-1319},
abstract={Managing the performance at the flow level through traffic measurement is crucial for effective network management. With the rapid rise in link speeds, collecting all packets has become difficult, so packet sampling has been attracting attention as a scalable means of measuring flow statistics. In this paper, we firstly propose a method of estimating TCP flow rates of sampled flows through packet sampling, and then develop a method of detecting performance degradation at the TCP flow level from the estimated flow rates. In the method of estimating flow rates, we use sequence numbers of sampled packets, which make it possible to improve markedly the accuracy of estimating the flow rates of sampled flows. Using both an analytical model and measurement data, we show that this method gives accurate estimations. We also show that, by observing the estimated rates of sampled flows, we can detect TCP performance degradation. The method of detecting performance degradation is based on the following two findings: (i) sampled flows tend to have high flow-rates and (ii) when a link becomes congested, the performance of high-rate flows becomes degraded first. These characteristics indicate that sampled flows are sensitive to congestion, so we can detect performance degradation of flows that are sensitive to congestion by observing the rate of sampled flows. We also show the effectiveness of our method using measurement data.},
keywords={},
doi={10.1093/ietcom/e91-b.5.1309},
ISSN={1745-1345},
month={May},}
부
TY - JOUR
TI - Packet Sampling TCP Flow Rate Estimation and Performance Degradation Detection Method
T2 - IEICE TRANSACTIONS on Communications
SP - 1309
EP - 1319
AU - Ryoichi KAWAHARA
AU - Tatsuya MORI
AU - Keisuke ISHIBASHI
AU - Noriaki KAMIYAMA
AU - Hideaki YOSHINO
PY - 2008
DO - 10.1093/ietcom/e91-b.5.1309
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E91-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2008
AB - Managing the performance at the flow level through traffic measurement is crucial for effective network management. With the rapid rise in link speeds, collecting all packets has become difficult, so packet sampling has been attracting attention as a scalable means of measuring flow statistics. In this paper, we firstly propose a method of estimating TCP flow rates of sampled flows through packet sampling, and then develop a method of detecting performance degradation at the TCP flow level from the estimated flow rates. In the method of estimating flow rates, we use sequence numbers of sampled packets, which make it possible to improve markedly the accuracy of estimating the flow rates of sampled flows. Using both an analytical model and measurement data, we show that this method gives accurate estimations. We also show that, by observing the estimated rates of sampled flows, we can detect TCP performance degradation. The method of detecting performance degradation is based on the following two findings: (i) sampled flows tend to have high flow-rates and (ii) when a link becomes congested, the performance of high-rate flows becomes degraded first. These characteristics indicate that sampled flows are sensitive to congestion, so we can detect performance degradation of flows that are sensitive to congestion by observing the rate of sampled flows. We also show the effectiveness of our method using measurement data.
ER -