svcadm(8)을 검색하려면 섹션에서 8 을 선택하고, 맨 페이지 이름에 svcadm을 입력하고 검색을 누른다.
cc_cdg(4)
CAIA-Delay Gradient (CDG) is a hybrid congestion control algo‐
rithm which reacts to both packet loss and inferred queuing de‐
lay. 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 there‐
fore incrementally deployable and suitable for use on shared net‐
works. 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 behaviour. CDG switches to loss-based operation when it de‐
tects that a configurable number of consecutive delay-based back‐
offs 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. The algorithm exposes the fol‐
lowing variables in the branch of the MIB: Current algorithm/im‐
plementation version number. Delay-based window decrease factor
as a percentage (on delay-based backoff, w = w * beta_delay /
100). Default is 70. Loss-based window decrease factor as a
percentage (on loss-based backoff, w = w * beta_loss / 100). De‐
fault is 50. Scaling parameter for the probabilistic exponential
backoff. Default is 2. Number of samples used for moving aver‐
age smoothing (0 means no smoothing). Default is 8. Number of
consecutive delay-gradient based congestion episodes which will
trigger loss-based CC compatibility. Default is 5. Number of
consecutive delay-gradient based congestion episodes to hold the
window backoff for loss-based CC compatibility. Default is 5.
If non-zero, this enables an experimental mode where CDG's window
increase factor (alpha) is increased by 1 MSS every RTTs during
congestion avoidance mode. (Setting to 1 results in the most ag‐
gressive growth of the window increase factor over time. Use
higher values for slower growth.) Default is 0. 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 Commu‐
nity Foundation. The congestion control module first appeared in
The module was first released in 2011 by David Hayes whilst work‐
ing on the NewTCP research project at Swinburne University of
Technology's Centre for Advanced Internet Architectures, Mel‐
bourne, Australia. More details are available at:
http://caia.swin.edu.au/urp/newtcp/ The congestion control module
was written by This manual page was written by and The underlying
algorithm and parameter values are still a work in progress and
may not be optimal for some network scenarios.