Power-Delay Trade-off for Heterogenous Cloud Enabled Multi-UAV Systems

Unmanned aerial vehicles (UAVs) have been widely used in a range of compelling applications. However, some of them are incompetent in tackling with computation-intensive tasks due to limited processing capability and battery life. In this paper, we combine the mobile edge computing and traditional cloud computing techniques for offloading the tasks from multi-UAV systems. Specifically, we jointly optimize the task scheduling and resource allocation in the heterogeneous cloud architecture, where we strike a power-delay trade-off of the system relying on the queue theory and Lyapunov optimization, followed by its optimal strategy analysis in each time slot. Moreover, we conceive an iterative algorithm with a closed-form solution at each iteration round in order to reduce the computational complexity. Finally, numerical results demonstrate both the feasibility and effectiveness of our proposed scheme. This paper validates that the heterogeneous cloud structure can be the beneficial for improving quality-of-service performance of multi-UAV systems.