  Mobile agent networks, such as multi-UAV systems, are constrained by limited
resources. In particular, limited energy affects system performance directly,
such as system lifetime. It has been demonstrated in the wireless sensor
network literature that the communication energy consumption dominates the
computational and the sensing energy consumption. Hence, the lifetime of the
multi-UAV systems can be extended significantly by optimizing the amount of
communication data, at the expense of increasing computational cost. In this
work, we aim at attaining an optimal trade-off between the communication and
the computational energy. Specifically, we propose a mixed-integer optimization
formulation for a multi-hop hierarchical clustering-based self-organizing UAV
network incorporating data aggregation, to obtain an energy-efficient
information routing scheme. The proposed framework is tested on two
applications, namely target tracking and area mapping. Based on simulation
results, our method can significantly save energy compared to a baseline
strategy, where there is no data aggregation and clustering scheme.
