  Due to their inherent complexity, engineered wireless multihop ad hoc
communication networks represent a technological challenge. Having no mastering
infrastructure the nodes have to selforganize themselves in such a way that for
example network connectivity, good data traffic performance and robustness are
guaranteed. In this contribution the focus is on routing & congestion control.
First, random data traffic along shortest path routes is studied by simulations
as well as theoretical modeling. Measures of congestion like end-to-end time
delay and relaxation times are given. A scaling law of the average time delay
with respect to network size is revealed and found to depend on the underlying
network topology. In the second step, a distributive routing & congestion
control is proposed. Each node locally propagates its routing cost estimates
and information about its congestion state to its neighbors, which then update
their respective cost estimates. This allows for a flexible adaptation of
end-to-end routes to the overall congestion state of the network. Compared to
shortest-path routing, the critical network load is significantly increased.
