an delay of 2.7ms, 75th percentile delay of 5ms, and is less than 90ms 95%
of the total simulation time.
make drops less randomly distributed
while CoDel gets randomness from the
independence of drop intervals and
Dropping the Right Packets
Although most network analysis today
assumes connections with an unloaded 100-ms RTT, in practice RTTs vary.
Unless a path includes a satellite link,
RTTs in the one-second range are usually caused by bufferbloat, not the intrinsic path characteristics. At the consumer edge, few connections will have
less than a 30ms RTT. Since CoDel’s interval is weakly related to RTT, we tested the effectiveness of a 100-ms setting
over a wide range of likely RTTs and
report on the range from 10ms–500ms.
Figure 8 shows results for a variety
of traffic loads, sorted by RTT. Both
CoDel and RED keep the median delay
low, but CoDel has higher link utilizations and better drop-share fairness,
showing that CoDel’s design is more
effective at dropping the right
packets. CoDel’s utilization is very close to
that of Tail Drop (except for an RTT
of 500ms) but with much less delay.
CoDel’s performance metrics are not
significantly different between 30ms
and 200ms RTTs. Utilizations are
slightly less and have a larger range
as the RTT increases, because some
traffic loads have difficulty keeping
the larger pipe full. The 500ms RTT
utilization shows more variation, the
low end corresponding to single FTPs,
which have difficulty keeping a very
large pipe full.
Figure 9 compares the Jain fairness
index for the source-drop shares of
CoDel and RED for these runs. CoDel
consistently outperforms RED for this
metric. This seems to be, in part, because the changes to the original RED
This scenario roughly emulates a consumer edge for two (symmetric) bandwidths: 512KB and 1.5MB. The load
includes a two-way 64Kbps CBR (
VoIP-like), an infinite FTP as a download,
Web browsing at a rate of two connections per second, and uploads of small
FTPs—1MB with short idle periods ( 5
to 15 seconds, uniformly distributed)
between. The table lists results, where
“C” is CoDel and “T” is Tail Drop and
each link direction is shown separately.
Although CoDel never drops packets at
a higher rate than Tail Drop, it keeps a
much smaller queue and transfers similar amounts of data, offering encouragement for taming bufferbloat.
The experiments presented here
mainly consist of “forward” traffic
where all the data traffic is going in the
analyzed direction. Reverse traffic has
well-known issues of ack compression
or data pendulum, which tend to push
the delay up and the utilization down.
There are known mitigations to im-
prove the mixing of acks and data pack-
ets that will be performed in the home-
router implementation. Even the
unmitigated simulation experiments
showed acceptable performance.
manage the Right Queue
At this point, a savvy user could be
tempted to deploy CoDel through
Figure 9. Jain fairness for drop share, CoDel (shown in black) and ReD (shown in red).
Fairness Index of Source Drop Share
Consumer edge example.
C t C/t
18 73 25%
5. 8 25%
C t C/t
3. 5 4. 7 75%
8 49 17%
2. 5 56%