Agent-enabled task offloading in UAV-aided mobile edge computing

Abstract

With the appearance of various mobile applications, such as automatic driving and augmented reality, it is difficult for the power and computing ability of mobile terminals to satisfy user demands. Therefore, an increasing number of terminal devices are requesting computing resources on the edge cloud. Because an unmanned aerial vehicle (UAV) is quite flexible and closer to the user side, an UAV can be adopted to assist mobile edge computing (MEC) while executing task offloading, which may reduce the pressure on edge clouds. However, it is unreasonable for users to make blind requests for resources due to the information asymmetry between a user and a service provider, and thus the quality of experience of user may be reduced. In this paper, an agent is introduced into the offloading of computing tasks, and a novel framework of agent-enabled task offloading in UAV-aided MEC(UMEC) is put forth to help the user, UAV, and edge cloud execute the offloading of computing tasks. With the intelligence and perceptibility of an agent, a system model is formulated in this paper to guide the agent in obtaining the optimum computing offloading plan, with minimum task execution delay and energy consumption. Simulation results showed that the introduction of an agent may significantly reduce delay and energy consumption, and the effectiveness of agent has been illustrated.