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Optimizing communication and computation for multi-UAV information gathering applications

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journal contribution
posted on 05.01.2018, 10:52 by Mason Thammawichai, Sujit Baliyarasimhuni, Eric C. Kerrigan, Joao Borges de Sousa
Typical mobile agent networks, such as multi-UAV systems, are constrained by limited resources: energy, computing power, memory and communication bandwidth. In particular, limited energy affects system performance directly, such as system lifetime. Moreover, it has been demonstrated experimentally in the wireless sensor network literature that the total energy consumption is often dominated by the communication cost, i.e. the computational and the sensing energy are small compared to the communication energy consumption. For this reason, the lifetime of the network can be extended significantly by minimizing the communication distance as well as 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 multihop 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.



  • Aeronautical, Automotive, Chemical and Materials Engineering


  • Aeronautical and Automotive Engineering

Published in

IEEE Transactions on Aerospace and Electronic Systems


THAMMAWICHAI, M., 2017. Optimizing communication and computation for multi-UAV information gathering applications. IEEE Transactions on Aerospace and Electronic Systems, 54(2), pp. 601-615.


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