  Cooperative UAV networks are becoming increasingly popular in military and
civilian applications. Alas, the typical ad-hoc routing protocols, which aim at
finding the shortest path, lead to significant performance degradation because
of the 3-dimension highly-dynamic nature of UAV networks and the uneven
distribution of nodes across the network. This paper proposes OPAR, an
optimized predictive and adaptive routing protocol, to face this challenging
problem. We model the routing problem with linear programming (LP), where the
goal is to maximize network performance, considering the path lifetime and
path-length together. This model relies on a precise link lifetime prediction
mechanism. We support the LP problem with a lightweight algorithm to find the
optimized solution with a computation complexity of $O(|E|^2)$, where $|E|$ is
the number of network links. We evaluate the OPAR performance and compare it
with the well-known routing algorithms AODV, DSDV, and OLSR to cover a wide
range of proactive and reactive protocols as well as distance vector and
link-state techniques. We performed extensive simulations for different network
densities and mobility patterns using the ns-3 simulator. Results show that
OPAR prevents a high volume of routing traffic, increases the successful
delivery by more than $30\%$, improves the throughput $25\%$ on average, and
decreases the flow completion time by an average of $35\%$.
