Mean field approximation is a powerful technique to study the performance of large stochastic systems represented as interacting objects. Applications include load balancing models, epidemic spreading, cache replacement policies, or large-scale data centers, for which mean gives very accurate estimates transient steady-state behaviors. In series recent papers [9, 7], new and more approximation,...