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Evaluating the Potential of Bandwidth Estimators Xiliang Liu, Kaliappa Ravindran, and Dmitri Loguinov

Evaluating the Potential of Bandwidth Estimators

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Evaluating the Potential of Bandwidth Estimators. Xiliang Liu, Kaliappa Ravindran, and Dmitri Loguinov. Overview. Bandwidth Estimators. Background. Evaluation Procedures. Preliminary Results. Conclusions. Network Model in Bandwidth Estimation. RCV. SND. C1. C2. C3. CT. CT. CT. A2. - PowerPoint PPT Presentation

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Page 1: Evaluating the Potential of Bandwidth Estimators

Evaluating the Potential of Bandwidth Estimators

Xiliang Liu, Kaliappa Ravindran, and Dmitri

Loguinov

Page 2: Evaluating the Potential of Bandwidth Estimators

Overview

Background

Bandwidth Estimators

Evaluation Procedures

Preliminary Results

Conclusions

Page 3: Evaluating the Potential of Bandwidth Estimators

Network Model in Bandwidth Estimation

RCVRCVSND

CT

C1

CT

C2

CT

C3

SNDSND RCVRCV

C1C2

C3

A1 A3

A2

Bottleneck Link

Page 4: Evaluating the Potential of Bandwidth Estimators

Existing Techniques

• Design justification– Use single-hop path with constant rate fluid CT

to identify measurement rationale

• Performance evaluation – Compare to Router MRTG report

ri

ro

A

Page 5: Evaluating the Potential of Bandwidth Estimators

Problems

• A lot of factors can affect the measurement accuracy– Practical issues– Algorithmic problems

• Current performance evaluation is monolithic– Can not identify the source of measurement

errors– Less reproducible and even can be conflicting

Page 6: Evaluating the Potential of Bandwidth Estimators

Bandwidth Estimators and performance metric

• Avail-bw inference algorithm – Input: the probing

input and output– Output: Avail-bw

estimation result

• Performance metrics– Single-hop potential – Multi-hop robustness

C

BW Estimator

Input CTOutput CT

Arriving probing construction

DepartingProbing

construction

Page 7: Evaluating the Potential of Bandwidth Estimators

Measurement targets of Bandwidth Estimators

Input construction

10mb/s

Bandwidth Estimator

Output construction

Input Poisson cross-trafficOutput cross-traffic

Page 8: Evaluating the Potential of Bandwidth Estimators

Classification of Bandwidth Estimators

• Non-iterative estimators – Fixed probing input– Every probing produces an estimation– Delphi, Spruce, Pathchirp

• Iterative estimators– Adapt probing input to find the

construction that bring out AW.– Pathload, IGI/PTR, TOPP

Page 9: Evaluating the Potential of Bandwidth Estimators

Trace-driven testing

. . .

Input Probing Construction Compute Output Probing Construction

BW Estimator

Hop Capacity

Cross-traffic trace

?

Page 10: Evaluating the Potential of Bandwidth Estimators

Why not just do NS2 simulation.

• Need much longer trace and time

• Inter Probing pattern introduces ASTA bias

Page 11: Evaluating the Potential of Bandwidth Estimators

Results: Cross-traffic trace

Page 12: Evaluating the Potential of Bandwidth Estimators

Results for Spruce Estimator

Page 13: Evaluating the Potential of Bandwidth Estimators

Results for PTR Estimator

Page 14: Evaluating the Potential of Bandwidth Estimators

Results for IGI Estimator

Page 15: Evaluating the Potential of Bandwidth Estimators

Results for TOPP Estimator

Page 16: Evaluating the Potential of Bandwidth Estimators

Conclusion and Future Work

• Our testing procedure – Quickly and easily evaluate one

performance aspect of BW estimators– Provide guidance to choose better

tunable parameters.

• Ongoing work– Evaluating pathload and pathChirp– Understanding the phenomenon

observed

Page 17: Evaluating the Potential of Bandwidth Estimators