L
Liang Huang
Researcher at Zhejiang University of Technology
Publications - 55
Citations - 2041
Liang Huang is an academic researcher from Zhejiang University of Technology. The author has contributed to research in topics: Mobile edge computing & Computation offloading. The author has an hindex of 15, co-authored 48 publications receiving 796 citations. Previous affiliations of Liang Huang include The Chinese University of Hong Kong & Virginia Tech.
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Journal ArticleDOI
Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks
TL;DR: In this article, a Deep Reinforcement Learning-based Online Offloading (DROO) framework is proposed to optimize task offloading decisions and wireless resource allocation to the time-varying wireless channel conditions.
Journal ArticleDOI
Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks
TL;DR: In this article, a Deep Reinforcement Learning-based Online Offloading (DROO) framework is proposed to optimize task offloading decisions and wireless resource allocation to the time-varying wireless channel conditions.
Journal ArticleDOI
Joint Optimization of Service Caching Placement and Computation Offloading in Mobile Edge Computing Systems
TL;DR: A single edge server that assists a mobile user in executing a sequence of computation tasks is considered, and a mixed integer non-linear programming (MINLP) is formulated that jointly optimizes the service caching placement, computation offloading decisions, and system resource allocation.
Journal ArticleDOI
Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing
TL;DR: A Deep-Q Network (DQN) based task offloading and resource allocation algorithm for the MEC system is proposed and extensive numerical results show that the proposed DQN-based approach can achieve the near-optimal performance.
Journal ArticleDOI
Distributed Deep Learning-based Offloading for Mobile Edge Computing Networks
TL;DR: This paper proposes a distributed deep learning-based offloading (DDLO) algorithm for MEC networks, where multiple parallel DNNs are used to generate offloading decisions, and adopts a shared replay memory to store newly generated offload decisions.