Name
Title | ||
|---|---|---|
Deep Reinforcement Learning-Based Mode Selection and Resource Management for Green Fog Radio Access Networks. |
Abstract | ||
|---|---|---|
Fog radio access networks (F-RANs) are seen as potential architectures to support services of Internet of Things by leveraging edge caching and edge computing. However, current works studying resource management in F-RANs mainly consider a static system with only one communication mode. Given network dynamics, resource diversity, and the coupling of resource management with mode selection, resourc... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JIOT.2018.2871020 | IEEE Internet of Things Journal |
Keywords | Field | DocType |
Resource management,Power demand,Program processors,Device-to-device communication,Heuristic algorithms,Cloud computing,Internet of Things | Edge computing,Resource management,Network dynamics,Cache,Computer science,Computer network,User equipment,Network interface controller,Cloud computing,Distributed computing,Reinforcement learning | Journal |
Volume | Issue | ISSN |
6 | 2 | 2327-4662 |
Citations | PageRank | References |
12 | 0.50 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yaohua Sun | 1 | 153 | 9.72 |
| Mugen Peng | 2 | 2779 | 200.37 |
| Shiwen Mao | 3 | 2816 | 192.93 |