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UAV-enabled Edge Computing for Optimal Task Distribution in Target Tracking

Unmanned aerial vehicles (UAVs) are useful devices due to their great manoeuvrability for long-range outdoor target tracking. However, these tracking tasks can lead to sub-optimal performance due to high computation requirements and power constraints. To cope with these challenges, we design a UAV-based target tracking algorithm where computationally intensive tasks are offloaded to Edge Computing (EC) servers. We perform joint optimization by considering the trade-off between transmission energy consumption and execution time to determine optimal edge nodes for task processing and reliable tracking. The simulation results demonstrate the superiority of the proposed UAV-based target tracking on the predefined trajectory over several existing techniques.