Online computation offloading and trajectory scheduling for UAV-enabled wireless powered mobile edge computing

The unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) architecture is expected to be a powerful technique to facilitate 5G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer (WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things (IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energy-efficiency (EE) minimization problem is formulated. Due to non-convexity and the time domain coupling of the variables in the formulated problem, a low-complexity online computation offloading and trajectory scheduling algorithm (OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes.