This document summarizes Vern Paxson's 1997/1999 paper "End-to-End Internet Packet Dynamics". The paper studied packet reordering, loss, and bottleneck bandwidth on the Internet through analyzing packet traces collected in 1994 and 1995. It found significant levels of packet reordering due to route changes. Packet loss rates were around 2-5% but most connections experienced no loss. The paper introduced new techniques to measure bottleneck bandwidth and addressed challenges in accurate measurement.
Paxson's Paper on Measuring Internet Packet Dynamics
1. Vern Paxson’s Paper"
“End-to-End"
Internet Packet
Dynamics”, 1997/99
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2. How often are packets
dropped?"
How often are packets
reordered?"
:
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3. Why these
questions?
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4. 1. Understand the
Internet
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5. “
when you can measure what you are
speaking about, and express it in
numbers, you know something about
it; but when you cannot measure it,
when you cannot express it in
”
numbers, your knowledge is of a
meagre and unsatisfactory kind;
- Lord Kelvin
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6. 2. Model the Internet
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7. 3. Enable more
accurate evaluation
through simulations
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8. 4. Lead to a better
application/systems
design
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9. How often are packets
dropped?"
How often are packets
reordered?"
:
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10. How to answer these
questions?
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11. Collect lots of packet
traces"
Analyze the traces
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12. Trace collection:"
large number of flows"
a variety of sites"
many packets per
flow"
use TCP
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13. Why TCP:"
real-world traffic"
will not overload the
network
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14. Time between measurement is
Poisson distributed."
PASTA Theorem: Intuitively, if we
make n observations and k
observations is in some state S and
n-k in other states, then we can
assume prob of observing S is
approximately k/n.
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15. Two traces:"
N1: Dec94 "
N2: Nov-Dec95"
use tcpdump at sender +
receiver"
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16. 100 kB
Size of file transfered
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17. 21
Number of sites
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18. 20800
Number of trace pairs
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19. Part 1:"
The Unexpected
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22. N1
N2
36%
12%
Percentage of connections with
at least one out-of-order delivery
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23. N1
N2
2%
.3%
Percentage of data packets out-of-order
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24. N1
N2
.6%
.1%
Percentage of ACK packets out-of-order
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25. Data packets are
usually sent
closer together.
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26. From
To
15%
.2%
Percentage of packets out-of-order
to and from U of Colorado in N1.
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27. Route fluttering:
alternate packets
can take different
route to dest.
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28. Taken from Paxson’s PhD Thesis: Alternate routes
are taken for packets from WUSTL to U Mannheim
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29. Fig 1 from the paper, showing large gap and two slopes.
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30. T1
(new arrival)
Ethernet
(buffered packets)
Fig 1 from the paper, showing large gap and two slopes.
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31. Impact of Packet
Reordering
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32. Recap: TCP’s fast
retransmit
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33. S = 1000
S = 2000
S = 3000
S = 4000
A = 2000
S = 5000
A = 2000
A = 2000
A = 2000
S = 2000
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34. S = 1000
S = 2000
S = 3000
S = 4000
A = 2000
S = 5000
A = 2000
A = 2000
A = 2000
S = 2000
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35. Nd = 3 is a
conservative
choice.
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36. What if receiver
wait longer before
sending dup ack?
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37. S = 2000
W
S = 2000
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38. 1
2
5
Delivery Gap: "
time between receiving "
3
an out-of-order packet and "
the packet sent before it.
4
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39. Taken from Paxson’s PhD Thesis: CDF for delivery gap between reordered
packets.
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49. 1 in 5000
packet is corrupted
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50. 1 in 65536
corrupted packet goes undetected
using TCP checksum
(assuming each possible checksum is equally likely)
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51. 1 in 300million
Internet packet is corrupted "
and is undetected.
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52. Part 2:"
Bottleneck
Bandwidth
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100. Compression
event if ξ < .75
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101. N1
N2
50%
60%
Percentage of connection that experiences"
at least one compression event.
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102. N1
N2
50%
60%
Percentage of connection that experiences"
at least one compression event.
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103. 2
Average number of events per connection.
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104. Estimating
Available
Bandwidth
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105. Qb: time to transit the bottleneck"
ψi: expected time spent queuing behind
predecessor (derived from sending time)"
γi: diff between packet OTT and min OTT
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106. time packet i is sent
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