Paper Review
: Dynamic Behaviour of Slowly-Responsive
Congestion Control Algorithms
Reviewer : Seh Leng Lim
This paper is an attempt to
investigate the behaviour of slowly-responsive,
TCP-compatible congestion control algorithms under more realistic dynamic
network conditions, with the aim of answering the fundamental question of
whether these algorithms are safe to deploy in the Internet. This is because
currently, TCP compatibility condition refers only to static conditions, and
not dynamic ones like the Internet.
The main contribution of the
paper is its observation that in return for smoother transmission rates,
slowly-responsive congestion control (SlowCC)
algorithms lose throughput to faster ones (like TCP) under dynamic network
conditions, thereby not achieving long-term fairness. In fact, the
TCP-compatible algorithms all appeared to be safe for deployment, as the more
slowly responsive ones can be made to avoid causing the network to go into
persistent overload persistent loss rates on sudden bandwidth reductions by
incorporating a self-clocking mechanism based on packet conservation. The
research from this paper is useful to encourage support for alternative
congestion control algorithms which are TCP compatible and which respond more
slowly to congestion, thereby producing a smoother bandwidth usage profile.
These slowly-responsive TCP compatible algorithms are needed to provide
smoother bandwidth usage for streaming video and audio applications, which current
TCP is very poor at.
The key main ideas expounded
are:
(a) TCP compatible whereby a congestion control mechanism is TCP compatible if its
bandwidth usage, in the presence of a constant loss is the same as TCP.
(b) The idea of moving from a
TCP controlled world to one where there is no single dominant congestion
control mechanism and instead there is a wide variety of mechanisms tailored to
different application requirements.
I
think that the paper has a significant contribution (rating of 4) to the study
of alternative congestion control algorithms which are TCP compatible and
slowly-responsive in a dynamic environment. The authors made use of a
single-bottleneck “dumbbell” configuration for their experiments. The authors
ran stress tests which involve “square-wave” and “saw-toothed” patterns of
available bandwidth to benchmark the behaviour of SlowCC under these conditions. They studied characteristics
of the SlowCC such as stabilization time (defined as
the time for the packet loss rate to stabilize after the start of a sustained
period of high congestion, where the packet loss rate has stabilized if it is
within 1.5 times its steady-state value), long-term fairness bandwidth
fairness, transient fairness, bottleneck link utilization and smoothness of
transmission rates. Although the experiments are based on simulation, they are
actually stress tests which means that their settings may be worst than in
reality. Therefore, I see that their observation of the behaviour
of SlowCC in their experiments may provide the lower
bound for the behaviour of SlowCC
in the Internet.
The
fact that SlowCC will not disrupt the TCP dominated
Internet is not sufficient to attract users. I feel that the lack of
aggressiveness of SlowCC in utilizing new available
bandwidth is a huge drawback, and may discourage their adoption, unless
absolutely necessary. Therefore, to realize the author’s vision of a
TCP-compatible Internet world, much more research needs to be done to get SlowCC to achieve bandwidth fairness.
Researchers and builders who
build streaming audio and video applications will have a better appreciations
from this paper of the technical difficulties faced in using alternative
TCP-compatible congestion control algorithms over the Internet.