[1] After numerous extensions, chiefly the BCMP network it was thought local balance was a requirement for a product-form solution.
Motivated by the need to model biological neurons which have a point-process like spiking behaviour, he introduced the precursor of G-Networks, calling it the random neural network.
Harrison and R.J. Williams note that "virtually all of the models that have been successfully analyzed in classical queueing network theory are models having a so-called product-form stationary distribution"[9] More recently, product-form solutions have been published for Markov process algebras (e.g. RCAT in PEPA[11][12]) and stochastic petri nets.
[13][14] Martin Feinberg's deficiency zero theorem gives a sufficient condition for chemical reaction networks to exhibit a product-form stationary distribution.
[21] Mitrani offers exact solutions to some simple networks with overtaking, showing that none of these exhibit product-form sojourn time distributions.