Aggregate Traffic Performance with Active Queue Management and Drop from Tail. Christophe Diot, Gianluca Iannaccone, Martin May Sprint ATL, Universit à di Pisa, Activia www.sprintlabs.com. Active Queue Management. queue. average. instantaneous. drop size. function. sharp. RED.
Christophe Diot, Gianluca Iannaccone, Martin May
Sprint ATL, Universitàdi Pisa, Activia
Drop from Tail
Testbed and Drop from Tail
with CISCO routers (7500)
We use “recommended” RED and GRED parameters
Heterogeneous delays (120 to 180 ms)Experiments
16 to and Drop from Tail256 TCP connections sharing the bottleneck.
Experimental traffic generated by Chariot
long-lived TCP connections.
more “realistic” traffic mix:
90% short lived TCP connections (up to 20 packets)
10 % long lived TCP connections
1Mbps UDP in both casesTraffic characteristics
Aggregate goodput through a router and Drop from Tail
TCP and UDP loss rate
Queuing behaviorMetrics observed
On consecutive losses, clear advantage to GRED and GRED-I.
“gentle” modification solves many RED problems.
Oscillations: no clear winner. Traffic seems to be the determining factor.In summary ...
Maybe GRED-I is an option if one can find a “universal” exponential dropping function.
ECN will work with any scheme.
Not clear the solution is in the AQM space.From the ISP standpoint ...
www.agere.com (an example)
vendors support from 64k to 200k flows
everybody gets what he/she paid for
local signaling (end host to CPE)About Fair Queuing ...