Calibrated Bandit Learning for Decentralized Task Offloading in Ultra-Dense Networks-Reference-Cited by-同舟云学术

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Calibrated Bandit Learning for Decentralized Task Offloading in Ultra-Dense Networks

Published:2022-04 Issue:4 Volume:70 Page:2547-2560
ISSN:0090-6778
Container-title:IEEE Transactions on Communications
language:
Short-container-title:IEEE Trans. Commun.

Author:

Zhang Rui¹^ORCID,Cheng Peng²^ORCID,Chen Zhuo³^ORCID,Liu Sige⁴^ORCID,Vucetic Branka⁴^ORCID,Li Yonghui⁴^ORCID

Affiliation:

1. Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong, China

2. Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia

3. CSIRO DATA61, Sydney, NSW, Australia

4. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia

Funder

ARC

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/26/9758163/09715074.pdf?arnumber=9715074

Reference52 articles.

1. The Nonstochastic Multiarmed Bandit Problem

2. A Geometric Proof of Calibration

3. Asymptotically efficient adaptive allocation rules

4. Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling

5. Energy-Efficient Task Offloading for Time-Sensitive Applications in Fog Computing

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1. Secure and Multistep Computation Offloading and Resource Allocation in Ultradense Multitask NOMA-Enabled IoT Networks;IEEE Internet of Things Journal;2024-02-01

2. Fast Adaptive Task Offloading and Resource Allocation in Large-Scale MEC Systems via Multiagent Graph Reinforcement Learning;IEEE Internet of Things Journal;2024-01-01

3. Task Offloading in Edge Computing Using GNNs and DQN;Computer Modeling in Engineering & Sciences;2024

4. Offloading Dependent Tasks in Edge Computing With Unknown System-Side Information;IEEE Transactions on Services Computing;2023-11

5. Multiagent Meta-Reinforcement Learning for Optimized Task Scheduling in Heterogeneous Edge Computing Systems;IEEE Internet of Things Journal;2023-06-15

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