Reinforcement learning based online request scheduling framework for workload-adaptive edge deep learning inference

• Main Authors: TAN, Xinrui, LI, Hongjia, XIE, Xiaofei, GUO, Lu, ANSARI, Nirwan, HUANG, Xueqing, WANG, Liming, XU, Zhen, LIU, Yang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Edge computing; deep learning inference serving systems; efficient deep learning inference; reinforcement learning; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9442; https://ink.library.smu.edu.sg/context/sis_research/article/10442/viewcontent/RL_OnlineRequest_av.pdf
• Institution: Singapore Management University

The recent advances of deep learning in various mobile and Internet-of-Things applications, coupled with the emergence of edge computing, have led to a strong trend of performing deep learning inference on the edge servers located physically close to the end devices. This trend presents the challeng...