Drl-os: a deep reinforcement learning-based offloading scheduler in mobile edge computing

HIGHLIGHTS

• who: Ducsun Lim and colleagues from the The Department of Computer and Software, Hanyang University, Wangsimni-ro, Seoul, Republic of Korea have published the research: DRL-OS: A Deep Reinforcement Learning-Based Offloading Scheduler in Mobile Edge Computing, in the Journal: Sensors 2022, 22, x FOR PEER REVIEW of /2022/
• what: This study proposes a deep-reinforcement-learning-based offloading scheduler (DRL-OS) that considers the energy balance in selecting the method for performing a task such as local computing offloading or dropping. The approach described aimed to minimize a task latency and conducted rule . . .
  

   

  

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