Delay aware scheduling in UAV-enabled OFDMA mobile edge computing system

Abstract

In infrastructure-less scenarios such as rural environments, wild emergency response, military applications and disaster relief, unmanned aerial vehicles (UAVs) are capable of providing enhanced mobile edge computing (MEC) services for ground users. Although small latency is the most important advantage of MEC system, how to provide delay aware scheduling in UAV-enabled MEC system still remains unsolved. In this study, the authors investigate the delay aware scheduling problem in UAV-enabled orthogonal frequency division multiple access (OFDMA) MEC system and formulate two non-convex optimisation problems. Moreover, they consider uplink and downlink architecture with characteristics in different UAV-ground links and traffic load. Furthermore, they propose two novel multi-stages resource allocation algorithms, i.e. the JSPA-T and JSPA-F algorithms with respect to downlink transmit power allocation and sub-carrier assignment. The mathematical frameworks with duality theory based alternative search optimisation and successive approximation method are proposed. The simulation results validate the performance improvement of the proposed solutions as well as the fast converge behaviour and small computational complexity.