A Multi-Layer Heterogeneous Task Scheduling Strategy in UAVs-assisted MEC Networks

This paper studies the task scheduling problem in the multiple unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) system. In order to reflect the complexity and diversity of the system, we propose a multi-layer heterogeneous task scheduling strategy. The strategy allows system model to simulate arrival and service of tasks by applying heterogeneous M/M/1, M/M/c, and M/M/c/K classical queues. In order to better evaluate the proposed strategy, we obtain various performance measures. By trading off delay and energy consumption, a single-objective optimization problem with constraints is formulated. Then we introduce the penalty function method to transform the problem into a single-objective optimization problem without any constraints, and propose a hierarchical heterogeneous task scheduling optimization (HHTSO) algorithm to optimize the formulated problem. Theoretical analysis and simulation results show that the proposed algorithm is more effective in ensuring low delay and low energy consumption.