| 英文标题 | Deep reinforcement learning based offloading scheduling in mobile edge computing |
| 作者英文名 | Zhan Wenhan, Wang Jin, Zhu Qingxin, Duan Hancong, Ye Yalan |
| 机构英文名 | 1.a.School of Information & Software Engineering,b.School of Computer Science & Engineering,University of Electronic Science & Technology of China,Chengdu 611731,China;2.College of Engineering,Mathematics & Physical Sciences,University of Exeter,Exeter EX44RN,UK |
| 英文摘要 | Aiming at the problem of task offloading with dependency in mobile edge computing, this paper proposed a deep reinforcement learning based offloading scheduling method to minimize the execution time of mobile applications. This method described the process of task scheduling as a Markov decision process. It adopted a sequence to sequence deep neural network to represent the scheduling policy, and then trained the deep neural network with the proximal policy optimization method. Simulation results show that the proposed method has good convergence ability and outperforms six baseline algorithms in different environments, demonstrating the effectiveness and reliability of the proposed method. |
| 英文关键词 | mobile edge computing; computation offloading; task scheduling; deep reinforcement learning |