  A disordered medium is often constructed by $N$ points independently and
identically distributed in a $d$-dimensional hyperspace. Characteristics
related to the statistics of this system is known as the random point problem.
As $d \to \infty$, the distances between two points become independent random
variables, leading to its mean field description: the random link model. While
the numerical treatment of large random point problems pose no major
difficulty, the same is not true for large random link systems due to Euclidean
restrictions. Exploring the deterministic nature of the congruential
pseudo-random number generators, we present techniques which allow the
consideration of models with memory consumption of order O(N), instead of
$O(N^2)$ in a naive implementation but with the same time dependence $O(N^2)$.
