Details
Original language | English |
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Title of host publication | 2013 IFIP Networking Conference |
Subtitle of host publication | IFIP Networking 2013 |
Publication status | Published - 2013 |
Event | 2013 IFIP Networking Conference, IFIP Networking 2013 - Brooklyn, NY, United States Duration: 22 May 2013 → 24 May 2013 |
Publication series
Name | 2013 IFIP Networking Conference, IFIP Networking 2013 |
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Abstract
An extensive body of research deals with estimating the correlation and the Hurst parameter of Internet traffic traces. The significance of these statistics is due to their fundamental impact on network performance. The coverage of Internet traffic traces is, however, limited since acquiring such traces is challenging with respect to, e.g., confidentiality, logging speed, and storage capacity. In this work, we investigate how the correlation of Internet traffic can be reliably estimated from random traffic samples. These samples are observed either by passive monitoring within the network, or otherwise by active packet probes at end systems. We analyze random sampling processes with different inter-sample distributions and show how to obtain asymptotically unbiased estimates from these samples. We quantify the inherent limitations that are due to limited observations and explore the influence of various parameters, such as sampling intensity, network utilization, or Hurst parameter on the estimation accuracy. We design an active probing method which enables simple and lightweight traffic sampling without support from the network. We verify our approach in a controlled network environment and present comprehensive Internet measurements. We find that the correlation exhibits properties such as long range dependence as well as periodicities and that it differs significantly across Internet paths and observation times.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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2013 IFIP Networking Conference: IFIP Networking 2013. 2013. 6663503 (2013 IFIP Networking Conference, IFIP Networking 2013).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Estimating Traffic Correlations from Sampling and Active Network Probing
AU - Rizk, Amr
AU - Bozakov, Zdravko
AU - Fidler, Markus
PY - 2013
Y1 - 2013
N2 - An extensive body of research deals with estimating the correlation and the Hurst parameter of Internet traffic traces. The significance of these statistics is due to their fundamental impact on network performance. The coverage of Internet traffic traces is, however, limited since acquiring such traces is challenging with respect to, e.g., confidentiality, logging speed, and storage capacity. In this work, we investigate how the correlation of Internet traffic can be reliably estimated from random traffic samples. These samples are observed either by passive monitoring within the network, or otherwise by active packet probes at end systems. We analyze random sampling processes with different inter-sample distributions and show how to obtain asymptotically unbiased estimates from these samples. We quantify the inherent limitations that are due to limited observations and explore the influence of various parameters, such as sampling intensity, network utilization, or Hurst parameter on the estimation accuracy. We design an active probing method which enables simple and lightweight traffic sampling without support from the network. We verify our approach in a controlled network environment and present comprehensive Internet measurements. We find that the correlation exhibits properties such as long range dependence as well as periodicities and that it differs significantly across Internet paths and observation times.
AB - An extensive body of research deals with estimating the correlation and the Hurst parameter of Internet traffic traces. The significance of these statistics is due to their fundamental impact on network performance. The coverage of Internet traffic traces is, however, limited since acquiring such traces is challenging with respect to, e.g., confidentiality, logging speed, and storage capacity. In this work, we investigate how the correlation of Internet traffic can be reliably estimated from random traffic samples. These samples are observed either by passive monitoring within the network, or otherwise by active packet probes at end systems. We analyze random sampling processes with different inter-sample distributions and show how to obtain asymptotically unbiased estimates from these samples. We quantify the inherent limitations that are due to limited observations and explore the influence of various parameters, such as sampling intensity, network utilization, or Hurst parameter on the estimation accuracy. We design an active probing method which enables simple and lightweight traffic sampling without support from the network. We verify our approach in a controlled network environment and present comprehensive Internet measurements. We find that the correlation exhibits properties such as long range dependence as well as periodicities and that it differs significantly across Internet paths and observation times.
UR - http://www.scopus.com/inward/record.url?scp=84890809171&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84890809171
SN - 9783901882555
T3 - 2013 IFIP Networking Conference, IFIP Networking 2013
BT - 2013 IFIP Networking Conference
T2 - 2013 IFIP Networking Conference, IFIP Networking 2013
Y2 - 22 May 2013 through 24 May 2013
ER -