[PATCH] Proportional Rate Reduction for TCP.

This patch implements
 Proportional Rate Reduction (PRR) for TCP. PRR is an algorithm that
 determines TCP's sending rate in fast recovery. PRR avoids excessive window
 reductions and aims for the actual congestion window size at the end of
 recovery to be as close as possible to the window determined by the
 congestion control algorithm. PRR also improves accuracy of the amount of
 data sent during loss recovery.

The patch implements the recommended flavor of PRR called PRR-SSRB
(Proportional rate reduction with slow start reduction bound) and
replaces the existing rate halving algorithm. PRR improves upon the
existing Linux fast recovery under a number of conditions including:
  1) burst losses where the losses implicitly reduce the amount of
outstanding data (pipe) below the ssthresh value selected by the
congestion control algorithm and,
  2) losses near the end of short flows where application runs out of
data to send.

As an example, with the existing rate halving implementation a single
loss event can cause a connection carrying short Web transactions to
go into the slow start mode after the recovery. This is because during
recovery Linux pulls the congestion window down to packets_in_flight+1
on every ACK. A short Web response often runs out of new data to send
and its pipe reduces to zero by the end of recovery when all its packets
are drained from the network. Subsequent HTTP responses using the same
connection will have to slow start to raise cwnd to ssthresh. PRR on
the other hand aims for the cwnd to be as close as possible to ssthresh
by the end of recovery.

A description of PRR and a discussion of its performance can be found at
the following links:
- IETF Draft:
    http://tools.ietf.org/html/draft-mathis-tcpm-proportional-rate-reduction-01
- IETF Slides:
    http://www.ietf.org/proceedings/80/slides/tcpm-6.pdf
    http://tools.ietf.org/agenda/81/slides/tcpm-2.pdf
- Paper to appear in Internet Measurements Conference (IMC) 2011:
    Improving TCP Loss Recovery
    Nandita Dukkipati, Matt Mathis, Yuchung Cheng

Signed-off-by: Nandita Dukkipati <nanditad@google.com>
Signed-off-by: David S. Miller <davem@davemloft.net>