Tandem queueing systems often arise in wireless networks
modeling. Queueing models are very suitable for network performance
evaluation but the system complexity exponential growth (or state space
explosion) could make the analysis barely feasible. The paper presents
a comparative study of various methods of a state space reduction for
markovian arrival processes (MAP) and phase-type distributions (PH)
applied to tandem queueing systems. The applied methods include non-
linear optimization, EM-algorithm and linear minimization. While most
of the described algorithms are well-studied, a number of issues arises
when applying them to a tandem system of a real wireless network.
Particularly, it is shown that while all the algorithms could be applied
to tandems with a small number of queues, bigger tandems require ad-
ditional eort to get the appropriable results. Nevertheless, the results
presented show that the departure MAPs reduction may help to solve
the state space explosion problem.