The behavior of a connection transmitting packets into a network
according to a general additive-increase multiplicative-decrease
(AIMD) algorithm is investigated. It is assumed that loss of packets
occurs in clumps. When a packet is lost, a certain number of
subsequent packets are also lost (correlated losses). The stationary
behavior of this algorithm is analyzed when the rate of occurrence of
clumps becomes arbitrarily small. From a probabilistic point of view,
it is shown that exponential functionals associated to compound
Poisson processes play a key role. A formula for the fractional
moments and some density functions are derived. Analytically, to get
the explicit expression of the distributions involved, the natural
framework of this study turns out to be the $q$-calculus. Different
loss models are then compared using concave ordering. Quite
surprisingly, it is shown that, for a fixed loss rate, the correlated
loss model has a higher throughput than an uncorrelated loss model.