This research studied the time distribution between packet loss events in TCP connections using a testbed with varying bandwidths and packet loss rates. The results show that for ADSL and T1 connections, over 80% of congestion events occurred within 1 second or less. For an OC-1 connection, over 80% of events were within 0.25 seconds. The time between events was shorter for higher bandwidth links. To maximize bandwidth utilization, TCP would need a bandwidth estimation mechanism performing updates within 1 second for highly congested links.

1. 1. Introduction
REU 2006-Packet Loss Distributions of TCP using
Web100
Zoriel M. Salado, Mentors: Dr. Miguel A. Labrador and Cesar D. Guerrero
2. Methodology
3. Results
4. Conclusions
5. Acknowledgments
Department of Computer Science &
I want to thank to César D. Guerrero and Dr. Miguel A.
Labrador for their orientations and the National Science
Foundation for supporting this project.
TCP congestion control mechanism regulates the rate at
which packets are transmitted from sender to receiver.
When a packet loss occurs, TCP reduces the
transmission rate to avoid congestion. This reduction
does not consider the available bandwidth in the
connection, and so, it does not maximize bandwidth
utilization.
The motivation for this work is to provide a mechanism
to evaluate how often a bandwidth estimation has to be
performed for TCP to improve its congestion control
mechanism.
The objective of this research is to find the time
distribution between packet loss events in TCP
connections.
A TCP connection was establish and congested to obtain
time intervals between congestion events.
2.1. Tools
We set a Testbed composed with two end hosts
communicated by a router machine based on
Dummynet. Dummynet is a packet shaper that allows to
set different bandwidths, delays, packet loss rates, and
more.
Congestion events were induced by variation in the packet loss rate and by generating cross traffic
using MGEN. To read from the TCP connection the times when a congestion event occurs, we use
Web100. It is a Linux kernel patch that allows to monitor TCP variables.
Specifically, the readvar command gets the
current value of a Web100/TCP variable from
one connection using the connection id,
obtained from a graphical user tool called Gutil
shown on the right.
Using a python script, we timestamp every
congestion event read with readvar and used a
Matlab program to plot the results.
2.2. Testing scenarios
To induce congestion events into the network, we applied Poisson
Cross Traffic to a 75% rate of the pipe’s total capacity. A FTP
connection was established from server-client and a 3GB file
transfer was sent. From that connection, time between congestion
events was measured.
Bandwidth
Cross
Traffic
512 Kbps (ADSL) 377 Kbps
1.5 Mbps (DS1/T1) 1.1 Mbps
50 Mbps (OC-1) 37.5 Mbps
The Cumulative Distribution
Functions (CDF) for the studied
scenarios show that for less than two
second congestion intervals:
•For an ADSL connection, 83% of the
congestion events occurs is less than
1s.
•For a DS1/T1 connection, the same
83% of the congestion events occurs
in less than 0.5 seconds. Bandwidth: 512 Kbps Bandwidth: 1.5 Mbps
Bandwidth: 50 Mbps
•For a OC-1 connection,
we see that 80% and
more of the congestion
events occur in 0.25
seconds. In addition, in
a lower rate of packet
loss, congestion events
are more often than in
higher rates of packet
loss.
•The lower the bandwidth, the less number of
congestion events and the longer the time between
them. A low bandwidth increases the RTT (Round
Trip Time) and reduces the frequency in which TCP
reacts to congestion events.
•In a high bandwidth link the number of congestion
events decreases when the packet loss rate increases.
In this case, the RTT is affected not by the
transmission speed but by the packet loss rate.
•For high loaded links (75% cross traffic and significant
packet loss rates), a bandwidth estimation mechanism
to provide channel information to TCP, has to be
performed in less than 1 second. That is the time
between the majority of the congestion events.
PLR 0.01 0.05 0.10
Cong.
Events
401 608 815
PLR 0.01 0.05 0.10
Cong.
Events
1048 1596 1778
PLR 0.01 0.05 0.10
Cong.
Events
7976 4216 1488