Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system is\na prominent concept, where a UAV equipped with a MEC server is deployed to\nserve a number of terminal devices (TDs) of Internet of Things (IoT) in a\nfinite period. In this paper, each TD has a certain latency-critical\ncomputation task in each time slot to complete. Three computation strategies\ncan be available to each TD. First, each TD can operate local computing by\nitself. Second, each TD can partially offload task bits to the UAV for\ncomputing. Third, each TD can choose to offload task bits to access point (AP)\nvia UAV relaying. We propose a new optimization problem formulation that aims\nto minimize the total energy consumption including communication-related\nenergy, computation-related energy and UAV's flight energy by optimizing the\nbits allocation, time slot scheduling and power allocation as well as UAV\ntrajectory design. As the formulated problem is non-convex and difficult to\nfind the optimal solution, we solve the problem by two parts, and obtain the\nnear optimal solution with within a dozen of iterations. Finally, numerical\nresults are given to validate the proposed algorithm, which is verified to be\nefficient and superior to the other benchmark cases.\n