强化学习
计算机科学
马尔可夫决策过程
移动边缘计算
计算卸载
能源消耗
延迟(音频)
分布式计算
马尔可夫过程
GSM演进的增强数据速率
边缘计算
服务器
计算机网络
蜂窝网络
人工智能
工程类
统计
电气工程
电信
数学
作者
Chao Li,Junjuan Xia,Fagui Liu,Li Dong,Lisheng Fan,George K. Karagiannidis,Arumugam Nallanathan
出处
期刊:IEEE Transactions on Vehicular Technology
[Institute of Electrical and Electronics Engineers]
日期:2021-03-01
卷期号:70 (3): 2922-2927
被引量:85
标识
DOI:10.1109/tvt.2021.3058995
摘要
In this paper, we study a multiuser mobile edge computing (MEC) network, where tasks from users can be partially offloaded to multiple computational access points (CAPs). We consider practical cases where task characteristics and computational capability at the CAPs may be time-varying, thus, creating a dynamic offloading problem. To deal with this problem, we first formulate it as a Markov decision process (MDP), and then introduce the state and action spaces. We further design a novel offloading strategy based on the deep Q network (DQN), where the users can dynamically fine-tune the offloading proportion in order to ensure the system performance measured by the latency and energy consumption. Simulation results are finally presented to verify the advantages of the proposed DQN-based offloading strategy over conventional ones.
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