CapProbe: Inexpensive and Accurate Estimation of Narrow Link - - PowerPoint PPT Presentation

CapProbe: Inexpensive and Accurate Estimation of Narrow Link Capacity

Rohit Kapoor Ling-Jyh Chen

• M. Y. “Medy” Sanadidi

Mario Gerla

December 2003 UCLA Computer Science 2

CapProbe: The Main Idea

• Observation: Both expansion and compression of dispersion

involve queuing due to cross traffic:

• Dispersion expansion => second packet queued
• Dispersion compression => first packet queued
• Packet pair with minimal end-to-end delay sum, is likely to be

dispersed corresponding to narrow link capacity

• Looking for packet pair with minimal delay sum is inexpensive
• CapProbe appears accurate in most of our experiments,

simulations and measurements

• CapProbe fails under heavy (~>75%) utilization by non-

responsive (UDP) traffic

December 2003 UCLA Computer Science 3

Preliminary Simulation Results

• A packet pair provides two pieces of information
• Dispersion between the two packets
• End-to-end/Round trip delay of each packet
• CapProbe combines both pieces of information
• Calculate delay sum for each packet pair sample
• Dispersion at minimum delay sum reflects capacity

Capacity

0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045 0.005 1.6 3.2 4.8 6.4 8 Bandwidth Estimates (Mbps) Minimum Delay Sum (sec)

December 2003 UCLA Computer Science 4

CapProbe Filtered the Compression

• 6-hop path: capacities {10, 7.5, 5.5, 4, 6, 8} Mbps
• PP pkt size = 200 bytes, CT pkt size = 1000 bytes
• Path-Persistent TCP Cross-Traffic

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.6 3.2 4.8 6.4 8 Bandwidth Estimate (Mbps) Frequency

1Mbps 2Mbps 4Mbps

Over-Estimation

Cross Traffic Rate

Bandwidth Estimate Frequency

0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.01 1.6 3.2 4.8 6.4 8 Bandwidth Estimate (Mbps) Min Delay Sums (sec)

1Mbps 2Mbps 4Mbps

Cross Traffic Rate

Minimum Delay Sums

December 2003 UCLA Computer Science 5

CapProbe Filtered the Expansion

• PP pkt size = 500 bytes, CT pkt size = 500 bytes
• Non-Path-Persistent TCP Cross-Traffic

0.0021 0.0042 0.0063 1.6 3.2 4.8 6.4 8 Bandwidth Estimate (Mbps) Min Delay Sum (sec)

1Mbps 3Mbps

Minimum Delay Sums

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.6 3.2 4.8 6.4 8 Bandwidth Estimate (Mbps) Frequency

1Mbps 3Mbps

Under-Estimation

Bandwidth Estimate Frequency

December 2003 UCLA Computer Science 6

CapProbe Failed Under Intensive Non-Responsive

• r Deterministic Cross Traffic
• Non-Path-Persistent UDP Cross Traffic
• Only case where CapProbe does not work: Intensive

UDP; No correct sample is obtained

0.002 0.004 0.006 0.008 0.01 0.012 0.014 1.6 3.2 4.8 6.4 8 Bandwidth Estimate (Mbps) Min Delay Sums (sec)

1Mbps 2Mbps 3Mbps 4Mbps

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.6 3.2 4.8 6.4 8 Bandwidth Estimate (Mbps) Frequency

1Mbps 2Mbps 3Mbps 4Mbps

Minimum Delay Sums Estimate Frequency

December 2003 UCLA Computer Science 7

Internet Measurements

• Each experiment: 500 PP at 0.5s

intervals

• 100 experiments for each {Internet path,

nature of CT, narrow link capacity}

• OS also induces inaccuracy: being fixed!

Laptop3 Dummy Net Laptop1 PING Source/ Destination Internet Laptop2 Cross-Traffic

DummyNet Capacity % Measurements Within 5% of Capacity % Measurements Within 10% of Capacity % Measurements Within 20% of Capacity

500 kbps Yahoo 100 100 100 1 mbps Yahoo 95 95 100 5 mbps Yahoo 100 100 100 10 mbps Yahoo 60 100 100 20 mbps Yahoo 75 100 100 500 kbps Google 100 100 100 1 mbps Google 100 100 100 5 mbps Google 95 100 100 10 mbps Google 80 95 100 20 mbps Google 65 100 100

December 2003 UCLA Computer Science 8

Wireless Measurements

• Bad channel 

retransmission larger dispersions lower estimated capacity

802.11b Access Point Laptop1 PING Source/ Destination Internet Laptop2 Cross-Traffic 802.11b Connectivity

Experiment No. Capacity Estimated by CapProbe (kbps) Capacity Estimated by strongest mode (kbps)

1

5526.68 4955.02

2

5364.46 462.8

3

5522.26 4631.76

4

5369.15 5046.62

5

5409.85 449.73

• Results for Bluetooth-interfered 802.11b, TCP cross-traffic

December 2003 UCLA Computer Science 9

CapProbe: Work in Progress

• Enhancements for confidence level, and adaptive probing
• Probabilistic analysis to determine number of samples

required to get min sample, that is probe length

• Implementation in OS Kernel to reduce host inaccuracy
• Extensive Internet and Abilene (and NLANR testbed?)

measurements experiments

• Use within TCP: estimating capacity accurately may help