xref: /freebsd/share/man/man4/cc_cdg.4 (revision fa9896e082a1046ff4fbc75fcba4d18d1f2efc19)

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.Dd May 13, 2021
.Dt CC_CDG 4
.Os
.Sh NAME
.Nm cc_cdg
.Nd CDG Congestion Control Algorithm
.Sh DESCRIPTION
CAIA-Delay Gradient (CDG) is a hybrid congestion control algorithm which reacts
to both packet loss and inferred queuing delay.
It attempts to operate as a delay-based algorithm where possible, but utilises
heuristics to detect loss-based TCP cross traffic and will compete effectively
as required.
CDG is therefore incrementally deployable and suitable for use on shared
networks.
.Pp
During delay-based operation, CDG uses a delay-gradient based probabilistic
backoff mechanism, and will also try to infer non congestion related
packet losses and avoid backing off when they occur.
During loss-based operation, CDG essentially reverts to
.Xr cc_newreno 4 Ns - Ns like
behaviour.
.Pp
CDG switches to loss-based operation when it detects that a configurable number
of consecutive delay-based backoffs have had no measurable effect.
It periodically attempts to return to delay-based operation, but will keep
switching back to loss-based operation as required.
.Sh MIB Variables
The algorithm exposes the following variables in the
.Va net.inet.tcp.cc.cdg
branch of the
.Xr sysctl 3
MIB:
.Bl -tag -width ".Va exp_backoff_scale"
.It Va version
Current algorithm/implementation version number.
.It Va beta_delay
Delay-based window decrease factor as a percentage (on delay-based backoff, w =
w * beta_delay / 100).
Default is 70.
.It Va beta_loss
Loss-based window decrease factor as a percentage (on loss-based backoff, w =
w * beta_loss / 100).
Default is 50.
.It Va exp_backoff_scale
Scaling parameter for the probabilistic exponential backoff.
Default is 2.
.It Va smoothing_factor
Number of samples used for moving average smoothing (0 means no smoothing).
Default is 8.
.It Va loss_compete_consec_cong
Number of consecutive delay-gradient based congestion episodes which will
trigger loss-based CC compatibility.
Default is 5.
.It Va loss_compete_hold_backoff
Number of consecutive delay-gradient based congestion episodes to hold the
window backoff for loss-based CC compatibility.
Default is 5.
.It Va alpha_inc
If non-zero, this enables an experimental mode where CDG's window increase
factor (alpha) is increased by 1 MSS every
.Va alpha_inc
RTTs during congestion avoidance mode.
(Setting
.Va alpha_inc
to 1 results in the most aggressive growth of the window increase factor over
time.
Use higher
.Va alpha_inc
values for slower growth.)
Default is 0.
.El
.Sh SEE ALSO
.Xr cc_chd 4 ,
.Xr cc_cubic 4 ,
.Xr cc_dctcp 4 ,
.Xr cc_hd 4 ,
.Xr cc_htcp 4 ,
.Xr cc_newreno 4 ,
.Xr cc_vegas 4 ,
.Xr h_ertt 4 ,
.Xr mod_cc 4 ,
.Xr tcp 4 ,
.Xr khelp 9 ,
.Xr mod_cc 9
.Rs
.%A "D. A. Hayes"
.%A "G. Armitage"
.%T "Revisiting TCP Congestion Control using Delay Gradients"
.%J "Networking 2011 Proceedings, Part II"
.%D "May 2011"
.%P "328-341"
.Re
.Rs
.%A "N. Khademi"
.%A "G. Armitage"
.%T "Minimising RTT across homogeneous 802.11 WLANs with CAIA Delay-Gradient TCP (v0.1)"
.%R "CAIA Technical Report 121113A"
.%D "November 2012"
.%U "http://caia.swin.edu.au/reports/121113A/CAIA-TR-121113A.pdf"
.Re
.Sh ACKNOWLEDGEMENTS
Development and testing of this software were made possible in part by grants
from the FreeBSD Foundation and The Cisco University Research Program Fund, a
corporate advised fund of Silicon Valley Community Foundation.
.Sh HISTORY
The
.Nm
congestion control module first appeared in
.Fx 9.2 .
.Pp
The module was first released in 2011 by David Hayes whilst working on the
NewTCP research project at Swinburne University of Technology's Centre for
Advanced Internet Architectures, Melbourne, Australia.
More details are available at:
.Pp
http://caia.swin.edu.au/urp/newtcp/
.Sh AUTHORS
.An -nosplit
The
.Nm
congestion control module was written by
.An David Hayes Aq Mt david.hayes@ieee.org .
This manual page was written by
.An Lawrence Stewart Aq Mt lstewart@FreeBSD.org
and
.An Grenville Armitage Aq Mt garmitage@swin.edu.au .
.Sh BUGS
The underlying algorithm and parameter values are still a work in progress and
may not be optimal for some network scenarios.