Network Resource Allocation Strategy Based on UAV Cooperative Edge Computing

Abstract

Aiming at the problem that fixed mobile edge computing (MEC) server is difficult to meet the needs of mobile users and temporary computing services, this study proposes a network resource allocation strategy based on unmanned aerial vehicle (UAV) cooperative edge computing. First, a UAV-aided MEC scene is designed, and a single UAV with an MEC server is used to provide auxiliary computing services for ground multiusers. Then, an optimization model aiming at total system delay is constructed by considering the system communication model and calculation model. Finally, Deep Q-Network is used to solve the optimization problem to obtain the best resource allocation scheme. Based on the experimental platform, the proposed strategy is demonstrated and analyzed. The results show that when the number of user equipment is 40, the total delay is about 33s, which is 35.29%, 31.25%, and 15.38% lower than other comparison strategies and effectively reduces the computing delay of users.