Q-Learning Based Content Placement Method for Dynamic Cloud Content Delivery Networks
How to reduce the content placement cost of cloud content delivery networks (CCDNs) is a hot topic in recent years. Traditional content placement methods mainly reduce the cost of content placement by constructing delivery trees, but they cannot adapt to the dynamic deployment of cloud proxy servers...
Main Authors: | Yujie Liu, Dianjie Lu, Guijuan Zhang, Jie Tian, Weizhi Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8717626/ |
Similar Items
-
Collaborative Reinforcement Learning Based Route Planning for Cloud Content Delivery Networks
by: Mingxin He, et al.
Published: (2021-01-01) -
A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks
by: Mohammad A. Salahuddin, et al.
Published: (2018-01-01) -
Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks
by: Kai Xu, et al.
Published: (2018-01-01) -
Autonomous Cache Resource Slicing and Content Placement at Virtualized Mobile Edge Network
by: Guolin Sun, et al.
Published: (2019-01-01) -
Resource allocation in cloud and Content Delivery Network (CDN)
by: Ahvar, Shohreh
Published: (2018)