2019
DOI: 10.1016/j.future.2019.05.067
|View full text |Cite
|
Sign up to set email alerts
|

A general AI-defined attention network for predicting CDN performance

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 19 publications
0
2
0
Order By: Relevance
“…The complete list of the training hyper-parameters used for training is enlisted in Appendix A. 4. Observe state s τ from simulator.…”
Section: Drl Algorithmmentioning
confidence: 99%
See 1 more Smart Citation
“…The complete list of the training hyper-parameters used for training is enlisted in Appendix A. 4. Observe state s τ from simulator.…”
Section: Drl Algorithmmentioning
confidence: 99%
“…For this reason, cost and Quality of Service (QoS) optimization for video content delivery systems is an active research area. A lot of the research effort in this context is being placed on the optimization [3], and modeling [4] of Content Delivery systems' performance.…”
Section: Introductionmentioning
confidence: 99%