Task Computation Offloading for Multi-Access Edge Computing via Attention Communication Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Task Computation Offloading for Multi-Access Edge Computing via Attention Communication Deep Reinforcement Learning

Published:2023-07-01 Issue:4 Volume:16 Page:2985-2999
ISSN:1939-1374
Container-title:IEEE Transactions on Services Computing
language:
Short-container-title:IEEE Trans. Serv. Comput.

Author:

Li Kexin¹^ORCID,Wang Xingwei²^ORCID,He Qiang³^ORCID,Yang Mingzhou¹,Huang Min⁴^ORCID,Dustdar Schahram⁵^ORCID

Affiliation:

1. College of Computer Science and Engineering, Northeastern University, Shenyang, China

2. College of Computer Science and Engineering and State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China

3. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China

4. College of Information Science and Engineering, Northeastern University, Shenyang, China

5. Distributed Systems Group, TU Wien, Vienna, Austria

Funder

National Key R & D Program of China

National Natural Science Foundation of China

LiaoNing Revitalization Talents Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/4629386/10213383/10025797.pdf?arnumber=10025797

Reference46 articles.

1. Multiagent actor-critic for mixed cooperative-competitive environments;ryan;Proc 31st Int Conf Neural Inf Process Syst,2017

2. Distributed and Collective Deep Reinforcement Learning for Computation Offloading: A Practical Perspective

3. Large-Scale User-Assisted Multi-Task Online Offloading for Latency Reduction in D2D-Enabled Heterogeneous Networks

4. D2D Fogging: An Energy-Efficient and Incentive-Aware Task Offloading Framework via Network-assisted D2D Collaboration

5. Multi-Agent Reinforcement Learning Based Resource Management in MEC- and UAV-Assisted Vehicular Networks

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-layer collaborative task offloading optimization: balancing competition and cooperation across local edge and cloud resources;The Journal of Supercomputing;2024-08-28

2. TRUST-ME: Trust-Based Resource Allocation and Server Selection in Multi-Access Edge Computing;Future Internet;2024-08-04

3. A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches;Computer Science Review;2024-08

4. A Multi-Agent Reinforcement Learning-Based Task-Offloading Strategy in a Blockchain-Enabled Edge Computing Network;Mathematics;2024-07-19

5. Distributed Link Heterogeneity Exploitation for Attention-Weighted Robust Federated Learning in 6G Networks;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS);2024-05-20