Congestion on the Internet is an old problem but still a subject of intensive
research. The TCP protocol with its AIMD (Additive Increase and Multiplicative
Decrease) behavior hides very challenging problems; one of them is to
understand the interaction between a large number of users with delayed
feedback. This article will focus on two modeling issues of TCP which appeared
to be important to tackle concrete scenarios when implementing the model
proposed in [Baccelli McDonald Reynier 02] firstly the modeling of the maximum
TCP window size: this maximum can be reached quickly in many practical cases;
secondly the delay structure: the usual Little-like formula behaves really
poorly when queuing delays are variable, and may change dramatically the
evolution of the predicted queue size, which makes it useless to study
drop-tail or RED (Random Early Detection) mechanisms. Within proposed TCP
modeling improvements, we are enabled to look at a concrete example where RED
should be used in FIFO routers instead of letting the default drop-tail happen.
We study mathematically fixed points of the window size distribution and local
stability of RED. An interesting case is when RED operates at the limit when
the congestion starts, it avoids unwanted loss of bandwidth and delay
variations