  In many distributed systems, from cloud to sensor networks, different
configurations impact system performance, while strongly depending on the
network topology. Hence, topological changes may entail costly reconfiguration
and optimisation processes. This paper proposes a multi-agent solution for
recovering networks from node failures. To preserve the network topology, the
proposed approach relies on local information about the network's structure,
which is collected and disseminated at runtime. The paper studies two
strategies for distributing topological data: one based on Mobile Agents (our
proposal) and the other based on Trickle (a reference gossiping protocol from
the literature). These two strategies were adapted for our self-healing
approach to collect topological information for recovering the network; and
were evaluated in terms of resource overheads. Experimental results show that
both variants can recover the network topology, up to a certain node failure
rate, which depends on the network topology. At the same time, Mobile Agents
collect less information, focusing on local dissemination, which suffices for
network recovery. This entails less bandwidth overheads than when Trickle is
used. Still, Mobile Agents utilise more memory and exchange more messages,
during data-collection, than Trickle does. These results validate the viability
of the proposed self-healing solution, offering two variant implementations
with diverse performance characteristics, which may suit different application
domains.
