  This paper proposes an adaptive variant of Random Early Detection (RED)
gateway queue management for packet-switched networks via a discrete state
analog of the non-stationary Master Equation i.e. Markov process. The
computation of average queue size, which appeared in the original RED
algorithm, is altered by introducing a probability $P(l,t)$, which defines the
probability of having $l$ number of packets in the queue at the given time $t$,
and depends upon the previous state of the queue. This brings the advantage of
eliminating a free parameter: queue weight, completely. Computation of
transition rates and probabilities are carried out on the fly, and determined
by the algorithm automatically. Simulations with unstructured packets
illustrate the method, the performance of the adaptive variant of RED
algorithm, and the comparison with the standard RED.
