Epidemics-inspired techniques have received huge attention in recent years
from the distributed systems and networking communities. These algorithms and
protocols rely on probabilistic message replication and redundancy to ensure
reliable communication. Moreover, they have been successfully exploited to
support group communication in distributed systems, broadcasting, multicasting
and information dissemination in fixed and mobile networks. However, in most of
the existing work, the probability of infection is determined heuristically,
without relying on any analytical model. This often leads to unnecessarily high
transmission overheads.
In this paper we show that models of epidemic spreading in complex networks
can be applied to the problem of tuning and controlling the dissemination of
information in wireless ad hoc networks composed of devices carried by
individuals, i.e., human-based networks. The novelty of our idea resides in the
evaluation and exploitation of the structure of the underlying human network
for the automatic tuning of the dissemination process in order to improve the
protocol performance. We evaluate the results using synthetic mobility models
and real human contacts traces
