Traffic Management for the Available Bit Rate (ABR) Service in ...

If the mean ACR is not a good estimate of the \fair share," then the scheme
can result in considerable unfairness [20].
The exponential averaging of the rates may become biased towards the higher
rates. For example, consider two sources running at 1000 Mbps and 1 Mbps.
In any given interval, the rst source will send 1000 times more control cells
than the second source and so the exponentially weighted average is very likely
to be 1000 Mbps regardless of the value of the weight used for computing the
average.
The problem is that the exponential averaging technique (which is similar to
the arithmetic mean) is not the right way to average a set of ratios (like ACRs
=number of cells/time) where the denominators are not equal [49]. We address
this averaging issue in the design of ERICA later in this dissertation.
The scheme uses queue length thresholds for congestion detection. As a result, it
e ectively \guesses" the rate allocations when the queue value is zero, or above
the high threshold. We will argue later in this dissertation that the queue length
does not provide full information about the congestion at the switch, and hence
is not reliable as the primary metric for rate-based congestion control.
The scheme uses a number of parameters whose values are typically set con-
servatively. This technique trades o transient response time (time required
to reach the steady state after a change in network conditions). This means
that the utilization of the bottlenecks will be lower on the average compared to
aggressive allocation schemes. Further, when the network is constantly in the
state when demand and capacity are variable (no steady state), the performance
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