Collaborative Caching Relay Algorithm in Vehicular Networks Based on Recursive Deep Reinforcement Learning
Abstract
References
Index Terms
- Collaborative Caching Relay Algorithm in Vehicular Networks Based on Recursive Deep Reinforcement Learning
Recommendations
Collaborative caching relay algorithm based on recursive deep reinforcement learning in mobile vehicle edge network
AbstractWith the rapid development of Internet of vehicles (IoV) and the continuous emergence of vehicle information applications, the demand for content in vehicle networking is growing at an alarming speed. Mobile vehicular edge caching is regarded as ...
Deep reinforcement learning techniques for vehicular networks: Recent advances and future trends towards 6G
AbstractEmploying machine learning into 6G vehicular networks to support vehicular application services is being widely studied and a hot topic for the latest research works in the literature. This article provides a comprehensive review of ...
Selective Victim Caching: A Method to Improve the Performance of Direct-Mapped Caches
Although direct-mapped caches suffer from higher miss ratios as compared to set-associative caches, they are attractive for today's high-speed pipelined processors that require very low access times. Victim caching was proposed by Jouppi [1] as an ...
Comments
Information & Contributors
Information
Published In
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 12Total Downloads
- Downloads (Last 12 months)12
- Downloads (Last 6 weeks)0
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format