  Unmanned aerial vehicle (UAV)-assisted multi-access edge computing (MEC) has
become one promising solution for energy-constrained devices to meet the
computation demand and the stringent delay requirement. In this work, we
investigate a multiple UAVs-assisted two-stage MEC system in which the
computation-intensive and delay-sensitive tasks of mobile devices (MDs) are
cooperatively executed on both MEC-enabled UAVs and terrestrial base station
(TBS) attached with the MEC server. Specifically, UAVs provide the computing
and relaying services to the mobile devices. In this regard, we formulate a
joint task offloading, communication and computation resource allocation
problem to minimize the energy consumption of MDs and UAVs by considering the
limited communication resources for the uplink transmission, the computation
resources of UAVs and the tolerable latency of the tasks. The formulated
problem is a mixed-integer non-convex problem which is NP hard. Thus, we relax
the channel assignment variable from the binary to continuous values. However,
the problem is still non-convex due to the coupling among the variables. To
solve the formulated optimization problem, we apply the Block Successive
Upper-bound Minimization (BSUM) method which guarantees to obtain the
stationary points of the non-convex objective function. In essence, the
non-convex objective function is decomposed into multiple subproblems which are
then solved in a block-by-block manner. Finally, the extensive evaluation
results are conducted to show the superior performance of our proposed
framework.
