We overview LN, a novel solver introduced in the LINE soft-
ware package to analyze layered queueing network (LQN) models. The
novelty of the LN solver lies in its capability to analyze LQNs with a user-
defined combination of solution paradigms, including discrete-event and
stochastic simulation, continuous-time Markov chain analysis (CTMC),
normalizing constant evaluation (NC), matrix analytic methods (MAM),
mean-field approximations (FLUID), and mean-value analysis (MVA).
Being parametric in the solver used for each LQN layer, LN as a whole
enables the efficient computation of advanced performance metrics such
as marginal and joint state probabilities, response and passage time distributions, and transient measures, leveraging individual strengths of the
supported solution paradigms. We discuss in particular recent developments added to NC, the default layer solver of LN, which significantly
improve the solution of queueing network models obtained using loose
layering