bionic (4) cc_cdg.4freebsd.gz

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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.