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Evaluation and Characterization of Available Bandwidth Probing Techniques

Evaluation and Characterization of Available Bandwidth Probing Techniques. Ningning Hu, Department of Computer Science, Carnegie Mellon University, Pittsburgh. Peter Steenkiste, Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh.

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Evaluation and Characterization of Available Bandwidth Probing Techniques

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  1. Evaluation and Characterization of Available Bandwidth Probing Techniques Ningning Hu, Department of Computer Science,Carnegie Mellon University, Pittsburgh Peter Steenkiste, Department of Electrical and Computer Engineering,Carnegie Mellon University, Pittsburgh IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 21, NO. 6, AUGUST 2003

  2. Motivation The questions : What are good techniques for estimating available bandwidth and what factors affect the measurement accuracy are still open questions. Use modeling, measurements and simulations to better characterize the interaction between probing packets and the competing network traffic.

  3. Contributions • Develop a single-hop gap model . The packet pair gap can be used to accurately characterize the competing traffic. • Develop two packet pair techniques—initial gap increasing (IGI) and packet transmission rate (PTR)—to characterize the available bandwidth on a network path. • Explore how packet train parameters can affect the measurement accuracy. • Use simulations to quantify how various factors impact the accuracy of the algorithms in multihop networks.

  4. Single-Hop Gap Model Single-Hop Gap Model

  5. Single-Hop Gap Model

  6. Single-Hop Gap Model ---DQR ---JQR

  7. Single-Hop Gap Model • Probing Packet Trains ---IGI formula (for CT) ---PTR formula (for a_bw) The key to an accurate available bandwidth measurement algorithm is to find a gI value so that the probing packet train operates in the JQR.

  8. Single-Hop Gap Model • Testbed Illustration

  9. Single-Hop Gap Model • Effect of JQR: Capturing Competing Traffic:

  10. Single-Hop Gap Model

  11. Single-Hop Gap Model • Effect of DQR: Losing Competing Traffic:

  12. Single-Hop Gap Model Discussion There is a proportional relationship between the output gap and the competing traffic.

  13. IGI and PTR Algorithms • Impact of Input Gap gI

  14. IGI and PTR Algorithms • IGI and PTR Algorithms In their experiments, δis set to 0.1

  15. Comparative Evaluation • Network Paths • Use the following 3 methods to measure the available bandwidth: • IGI and PTR • Pathload • Bulk data transfer (Iperf)

  16. Comparative Evaluation Note: Link capacities are measured by bprob and the RTTs by ping.

  17. Comparative Evaluation • Measurement Accuracy

  18. Comparative Evaluation (P1) CORNELL -> MA

  19. Comparative Evaluation • Convergence Times

  20. IGI and PTR Algorithm Properties • Probing Packet Size

  21. IGI and PTR Algorithm Properties

  22. IGI and PTR Algorithm Properties • Small packet sizes can result in high errors in the available bandwidth estimation. • The resulting probing train is more sensitive to the burstiness of the competing traffic. • The small gap values are harder to measure accurately. • Probing flows with larger packets are more aggressive than probing flows with smaller packets, so they “observe” a higher available bandwidth. • The packet sizes that result in the closest estimates are 500 and 700 Byte.

  23. IGI and PTR Algorithm Properties • Packet Train Length and Number of Probing Phases NWU -> CMU 100Mbps CORNELL -> CMU 10Mbps

  24. IGI and PTR Algorithm Properties NWU -> CMU 100Mbps CORNELL -> CMU 10Mbps

  25. Multihop Effects

  26. Multihop Effects • Tight Link Is Not the Bottleneck Link

  27. Multihop Effects • Interference From Traffic on “Nontight” Links • Competing traffic before the tight link has almost no impact on the accuracy. Changes in gap values before the tight link can be reshaped by the router. • Competing traffic after the tight link does have an effect and, its impact increases with the level of competing traffic.

  28. Multihop Effects • Timing Errors Measurement errors on the destination side will have a more significant impact since they will directly change the gap values that are used in the IGI and PTR formulas.

  29. Conclusion • The authors present a simple gap model to identify under what conditions packet pairs probing yields useful information about the available bandwidth along a path. • They design IGI and PTR for estimating available bandwidth based on the gap model. • IGI and PTR have a shorter convergence time than Pathload.

  30. Conclusion • The probing packet size and packet train length are investigated to have a achieve the best measurement accuracy. • IGI method loses accuracy if the tight link is not the bottleneck link, or if there is significant competing traffic on links following the tight link.

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