Chinese Journal on Internet of Things ›› 2021, Vol. 5 ›› Issue (1): 27-35.doi: 10.11959/j.issn.2096-3750.2021.00190

Special Issue: 边缘计算

• Topic: Edge Intelligence and Fog Computing in IoT • Previous Articles     Next Articles

Joint task offloading and trajectory optimization for multi-UAV assisted mobile edge computing

Jiequ JI, Kun ZHU, Changyan YI, Ran WANG   

  1. Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Revised:2021-02-06 Online:2021-03-30 Published:2021-03-01
  • Supported by:
    The National Natural Science Foundation of China(62071230);The National Natural Science Foundation of China(62061146002)

Abstract:

An unmanned aerial vehicle (UAV)-assisted mobile edge computing system was proposed in which multiple UAVs equipped with computing resources were employed to provide computation offloading opportunities for mobile users with limited local resources.The computing tasks of each user can be divided into two parts.One portion was offloaded to its associated UAV for computing and the remaining portion was processed locally.It was aimed at minimizing the sum of the maximum delay among all user devices by jointly optimizing the user scheduling and the UAV trajectory in a finite period.The proposed problem was a mixed-integer non-convex optimization problem.To facilitate solving this problem, it was equivalently converted into a more tractable problem by introducing some auxiliary variables, and then a penalty concave-convex procedure algorithm was proposed to solve the converted problem.Simulation results show that the proposed joint optimization scheme achieves significantly better performance than other benchmark schemes.

Key words: unmanned aerial vehicle, mobile edge computing, trajectory design, user scheduling

CLC Number: 

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