  The problem of finding a resource residing in a network node (the
\emph{resource location problem}) is a challenge in complex networks due to
aspects as network size, unknown network topology, and network dynamics. The
problem is especially difficult if no requirements on the resource placement
strategy or the network structure are to be imposed, assuming of course that
keeping centralized resource information is not feasible or appropriate. Under
these conditions, random algorithms are useful to search the network. A
possible strategy for static networks, proposed in previous work, uses short
random walks precomputed at each network node as partial walks to construct
longer random walks with associated resource information. In this work, we
adapt the previous mechanisms to dynamic networks, where resource instances may
appear in, and disappear from, network nodes, and the nodes themselves may
leave and join the network, resembling realistic scenarios. We analyze the
resulting resource location mechanisms, providing expressions that accurately
predict average search lengths, which are validated using simulation
experiments. Reduction of average search lengths compared to simple random walk
searches are found to be very large, even in the face of high network
volatility. We also study the cost of the mechanisms, focusing on the overhead
implied by the periodic recomputation of partial walks to refresh the
information on resources, concluding that the proposed mechanisms behave
efficiently and robustly in dynamic networks.
