  Wireless sensor networks are an important technology for making distributed
autonomous measures in hostile or inaccessible environments. Among the
challenges they pose, the way data travel among them is a relevant issue since
their structure is quite dynamic. The operational topology of such devices can
often be described by complex networks. In this work, we assess the variation
of measures commonly employed in the complex networks literature applied to
wireless sensor networks. Four data communication strategies were considered:
geometric, random, small-world, and scale-free models, along with the shortest
path length measure. The sensitivity of this measure was analyzed with respect
to the following perturbations: insertion and removal of nodes in the geometric
strategy; and insertion, removal and rewiring of links in the other models. The
assessment was performed using the normalized Kullback-Leibler divergence and
Hellinger distance quantifiers, both deriving from the Information Theory
framework. The results reveal that the shortest path length is sensitive to
perturbations.
