  The bigraph theory is a relatively young, yet formally rigorous, mathematical
framework encompassing Robin Milner's previous work on process calculi, on the
one hand, and provides a generic meta-model for complex systems such as
multi-agent systems, on the other. A bigraph $F = \langle F^P, F^L\rangle$ is a
superposition of two independent graph structures comprising a place graph
$F^P$ (i.e., a forest) and a link graph $F^L$ (i.e., a hypergraph), sharing the
same node set, to express locality and communication of processes independently
from each other.
  In this paper, we take some preparatory steps towards an algorithm for
generating random bigraphs with preferential attachment feature w.r.t. $F^P$
and assortative (disassortative) linkage pattern w.r.t. $F^L$. We employ
parameters allowing one to fine-tune the characteristics of the generated
bigraph structures. To study the pattern formation properties of our
algorithmic model, we analyze several metrics from graph theory based on
artificially created bigraphs under different configurations.
  Bigraphs provide a quite useful and expressive semantic for process calculi
for mobile and global ubiquitous computing. So far, this subject has not
received attention in the bigraph-related scientific literature. However,
artificial models may be particularly useful for simulation and evaluation of
real-world applications in ubiquitous systems necessitating random structures.
