LAUSR

As a technique to buffer the conflict between computation-intensive tasks and capability-limited devices, unmanned aerial vehicle-enabled mobile-edge computing (UAV-MEC) has been witnessed as a promising approach, especially in the post-disaster scenario where the infrastructure is limited or unavailable. In this article, we consider a joint optimization of topology reconstruction and subtask scheduling to minimize the average completion time of the subtask. To address this problem, we propose a hierarchical hybrid subtask scheduling algorithm (H-HSS). First, a topology reconstruction game algorithm for energy-efficient control (TRGE) is investigated to get optimal power and node-to-node connection decision, in which the interaction between the node with its neighbors is modeled as a single-leader–multifollowers Stackelberg game. Second, by analyzing the dependency between subtasks, a hierarchical-dependent subgraph extraction scheme (HDSE) is proposed, which transforms the subtask call graph into a hierarchical tree diagram to obtain a hierarchical scheduling list. Finally, a hybrid subtask scheduling scheme is presented to make optimal task scheduling decisions. Numerical results show that H-HSS can significantly outperform the other representative benchmarks with low complexity, in subtask completion time, energy consumption, or weighted sum. In addition, the tolerance capability of our proposed TRGE algorithm is increased by 66%.