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

For example, overload depends upon the ABR capacity and is used in the formula
to achieve max-min fairness. Since the ERICA+ algorithm changes the ABR capacity
depending upon the queue lengths, this formula needs to tolerate minor changes in
load factor. In fact, the formula applies hysteresis to eliminate the variation due
to the load factor. Since techniques like hysteresis and averaging can tolerate only a
small amount ofvariation, we need to reduce the variance in the target ABR capacity.
We examine the ABR capacity term rst. ABR capacity is estimated over the av-
eraging interval of ERICA. A simple estimation process can entail counting the VBR
cells sent, calculating the VBR capacity, and subtracting it from the link capacity.
This process may have an error of one VBR cell divided by the averaging interval
length. The error can be minimized by choosing longer averaging intervals.
However, the measured ABR capacity has less variance than instantaneous queue
lengths. This is because averages of samples have less variance than the samples
themselves, and ABR capacity is averaged over an interval, whereas queue length is
not. The quantity Q0 = T 0 ABRCapacity has the same variance as that of the
measured ABR capacity.
We now examine the function, f(Tq). This function is bounded below by QDLF
and above by b. Hence, its values lie in the range (QDLF,b) or, in practice, in the
range (0.5, 1.05). Further, it has variance because it depends upon the queue length,
q and the quantity Q0. Since the function includes a ratio of Q0 andq, ithashigher
variance than both quantities.
One way to reduce the variance is to use an averaged value of queue length (q),
instead of the instantaneous queue length. Asimpleaverage is the mean of the queue
lengths at the beginning and the end of a measurement interval. This is su cient for
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