Energy-Delay Tradeoff for Online Offloading Based on Deep Reinforcement Learning in Wireless Powered Mobile-Edge Computing Networks

• 作者: WANG Zhonglin CAO Hankai ZHAO Ping RAO Wei
• 来源期刊: 东华大学学报（英文版）
• 学科: 工学
• 年，卷（期）: 2020,（6）
• 页码范围: 498-503
• 页数: 6页
• 分类号: TP391.9
• 语种: 英文
• DOI: 10.19884/j.1672-5220.202009072

摘要

Benefited from wireless power transfer ( WPT ) and mobile-edge computing ( MEC ) , wireless powered MEC systems have attracted widespread attention. Specifically, we design an online offloading scheme based on deep reinforcement learning that maximizes the computation rate and minimizes the energy consumption of all wireless devices ( WDs) . Extensive results validate that the proposed scheme can achieve better tradeoff between energy consumption and computation delay.