Name
Title | ||
|---|---|---|
Deep-Reinforcement-Learning-Based Latency Minimization in Edge Intelligence Over Vehicular Networks |
Abstract | ||
|---|---|---|
A novel paradigm that combines federated learning with blockchain to empower edge intelligence over vehicular networks (FBVN) can enable latency-sensitive deep neural network-based applications to be executed in a distributed pattern. However, the complex environments in FBVN make the system latency much harder to minimize by traditional methods. In this article, we model the training and transmis... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/JIOT.2021.3078480 | IEEE Internet of Things Journal |
Keywords | DocType | Volume |
Collaborative work,Blockchain,Training,Wireless communication,Internet of Things,Wireless sensor networks,Vehicle dynamics | Journal | 9 |
Issue | ISSN | Citations |
2 | 2327-4662 | 0 |
PageRank | References | Authors |
0.34 | 39 | 6 |