NAME

     cc_cdg — CDG Congestion Control Algorithm

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.

     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
     cc_newreno(4)-like behaviour.

     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.

MIB Variables

     The algorithm exposes the following variables in the net.inet.tcp.cc.cdg branch of the
     sysctl(3) MIB:

     version            Current algorithm/implementation version number.

     beta_delay         Delay-based window decrease factor as a percentage (on delay-based
                        backoff, w = w * beta_delay / 100).  Default is 70.

     beta_loss          Loss-based window decrease factor as a percentage (on loss-based backoff,
                        w = w * beta_loss / 100).  Default is 50.

     exp_backoff_scale  Scaling parameter for the probabilistic exponential backoff.  Default is
                        2.

     smoothing_factor   Number of samples used for moving average smoothing (0 means no
                        smoothing).  Default is 8.

     loss_compete_consec_cong
                        Number of consecutive delay-gradient based congestion episodes which will
                        trigger loss-based CC compatibility.  Default is 5.

     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.

     alpha_inc          If non-zero, this enables an experimental mode where CDG's window
                        increase factor (alpha) is increased by 1 MSS every alpha_inc RTTs during
                        congestion avoidance mode.  (Setting alpha_inc to 1 results in the most
                        aggressive growth of the window increase factor over time.  Use higher
                        alpha_inc values for slower growth.)  Default is 0.

SEE ALSO

     cc_chd(4), cc_cubic(4), cc_hd(4), cc_htcp(4), cc_newreno(4), cc_vegas(4), h_ertt(4),
     mod_cc(4), tcp(4), khelp(9), mod_cc(9)

     D. A. Hayes and G. Armitage, “Revisiting TCP Congestion Control using Delay Gradients”,
     Networking 2011 Proceedings, Part II, 328-341, May 2011.

     N. Khademi and G. Armitage, Minimising RTT across homogeneous 802.11 WLANs with CAIA Delay-
     Gradient TCP (v0.1), CAIA Technical Report 121113A,
     http://caia.swin.edu.au/reports/121113A/CAIA-TR-121113A.pdf, November 2012.

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.

HISTORY

     The cc_cdg congestion control module first appeared in FreeBSD 9.2.

     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:

     http://caia.swin.edu.au/urp/newtcp/

AUTHORS

     The cc_cdg congestion control module was written by David Hayes <david.hayes@ieee.org>.
     This manual page was written by Lawrence Stewart <lstewart@FreeBSD.org> and Grenville
     Armitage <garmitage@swin.edu.au>.

BUGS

     The underlying algorithm and parameter values are still a work in progress and may not be
     optimal for some network scenarios.