Cooperative Computation and Cache Scheduling for UAV-Enabled MEC Networks

Since the flight of Unmanned Aerial Vehicle (UAV) greatly consumes the limited on-board energy and affects the ability to afford computation services, it is urgent and challenging to minimize UAV’s endurance time while satisfying varieties of constraints from the UAVs and users, such as energy budgets, cache capacities, computation resources, and latency requirements. In this paper, the UAVs are endowed with the capability to temporarily buffer some offloaded tasks and process them later, then adopt cooperative computation and cache scheduling to minimize their total endurance time. Following this, the formulated problem is a mix-integer nonlinear programming problem, which can be further transformed into three more tractable subproblems: 1) $\mathbf {P_{O}}$ , offloading decision and scheduling strategy for computing & caching; 2) $\mathbf {P_{H}}$ , hovering trajectory design; and 3) $\mathbf {P_{C}}$ , computation resource allocation, and then iteratively tackled in a sequence. Due to the high complexity of solving $\mathbf {P_{O}}$ , the low-complexity algorithm based on the ${K}$ -means clustering and Penalty Method is proposed to reduce complexity and facilitate the processing procedure, which can save about 91.04%–189.36% running time and ONLY sacrifice 8.05%–22.08% of the total endurance time. Simulation results show that cooperative computation and cache scheduling has a great effect on saving endurance time.