  Unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS)
have been recently applied in the field of mobile edge computing (MEC) to
improve the data exchange environment by proactively changing the wireless
channels through maneuverable location deployment and intelligent signals
reflection, respectively. Nevertheless, they may suffer from inherent
limitations in practical scenarios. UAV-mounted RIS (U-RIS), as a promising
integrated approach, can combine the advantages of UAV and RIS to break the
limit. Inspired by this, we consider a novel U-RIS assisted MEC system, where a
U-RIS is deployed to assist the communication between the ground users and an
MEC server. The joint UAV trajectory, RIS passive beamforming and MEC resource
allocation design is developed to maximize the energy efficiency (EE) of the
system. To tackle the intractable non-convex problem, we divide it into two
subproblems and solve them iteratively based on successive convex approximation
(SCA) and the Dinkelbach method. Finally we obtain a high-performance
suboptimal solution. Simulation results show that the proposed algorithm
significantly improves the energy efficiency of the MEC system.
