Latency Minimization for Multi-UAV Aided Mobile Edge Computing

Mobile edge computing (MEC) is a paradigm that supports resource-intensive applications on mobile devices by offloading the tasks to edge servers. This paper considers a multi unmanned aerial vehicle (UAV)-mounted MEC framework, in which each device opts for offloading all or a fraction of its computational tasks to the UAV-mounted MEC servers. To enable simultaneous offloading from the devices to MEC servers, a non-orthogonal multiple access transmission is considered such that each device transmits a superposed message and a successive interference cancellation enabled decoding is performed at each MEC server. A min-max latency minimization problem is for-mulated to optimize the UAV s' placement, the power allocation of each device, and the offloading volume from each device to the servers. An alternating optimization approach based on the block coordinate descent (BCD) technique is developed. A more computationally efficient heuristic solution is also introduced, which involves
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-means clustering and e-scaled power allocation. Numerical results illustrate that the heuristic solution provides a good performance close to the BCD technique performance. Results also demonstrate the effectiveness of the considered framework compared to the device- Uavassociation scenario, in which each device is assigned to only one UAV-mounted server.