DQN Approach for Adaptive Self-Healing of VNFs in Cloud-Native Network-Reference-Cited by-同舟云学术

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DQN Approach for Adaptive Self-Healing of VNFs in Cloud-Native Network

Published:2024 Issue: Volume:12 Page:34489-34504
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Arulappan Arunkumar¹^ORCID,Mahanti Aniket²^ORCID,Passi Kalpdrum³^ORCID,Srinivasan Thiruvenkadam⁴^ORCID,Naha Ranesh⁵^ORCID,Raja Gunasekaran⁶^ORCID

Affiliation:

1. School of Computer Science Engineering and Information Systems, VIT University, Vellore, India

2. School of Computer Science, The University of Auckland, Auckland, New Zealand

3. School of Engineering and Computer Science, Laurentian University, Sudbury, ON, Canada

4. School of Electrical Engineering, VIT University, Vellore, India

5. Centre for Smart Analytics, Federation University Australia, Melbourne, VIC, Australia

6. Department of Computer Technology, NGNLab, Anna University, MIT Campus, Chennai, India

Funder

School of Engineering and Computer Science, Laurentian University, Sudbury, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10433492.pdf?arnumber=10433492

Reference26 articles.

1. Graph Convolutional Reinforcement Learning for Collaborative Queuing Agents

2. A Deep Reinforcement Learning Approach to Traffic Signal Control With Temporal Traffic Pattern Mining

3. IEACC: An Intelligent Edge-Aided Congestion Control Scheme for Named Data Networking With Deep Reinforcement Learning

4. NFV Data Centers: A Systematic Review

5. Joint Optimization of Resource Allocation and Service Performance in vEPC Using Reinforcement Learning

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