Quality of service optimization algorithm based on deep reinforcement learning in software defined network
Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have problems such as slow convergence and instability.A...
Saved in:
Main Authors: | Cenhuishan LIAO, Junyan CHEN, Guanping LIANG, Xiaolan XIE, Xiaoye LU |
---|---|
Format: | Article |
Language: | zho |
Published: |
China InfoCom Media Group
2023-03-01
|
Series: | 物联网学报 |
Subjects: | |
Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00316/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research and application of traffic engineering algorithm based on deep learning
by: Daoyun HU, et al.
Published: (2021-02-01) -
Enhancing Quality of Service in Software-Defined Internet of Things (SD-IoT) Environment: A review
by: Grif Abdelali, et al.
Published: (2024-01-01) -
PriQoS:priority-differentiated flow control mechanism based on SDN
by: Zhi SUN, et al.
Published: (2017-02-01) -
Quality of Service of Routing Protocols in Wireless Sensor Networks: A Review
by: Muhammad Asif, et al.
Published: (2017-01-01) -
QoS routing algorithm based on multiple domain architecture of SDN
by: Wei HUANG, et al.
Published: (2019-10-01)