Name
Title | ||
|---|---|---|
Deep Learning-Assisted Energy-Efficient Task Offloading in Vehicular Edge Computing Systems |
Abstract | ||
|---|---|---|
In this paper, we study an energy-efficient computation offloading for vehicular edge computing systems, where multiple roadside units assist vehicular users to offload computation tasks to edge servers. Our goal is to minimize the users’ energy consumption by optimizing user association, data partition, transmit power, and computation resources, subject to the constraints of partial tasks offload... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TVT.2021.3090179 | IEEE Transactions on Vehicular Technology |
Keywords | DocType | Volume |
Servers,Task analysis,Fading channels,Energy consumption,Computational modeling,Resource management,Data models | Journal | 70 |
Issue | ISSN | Citations |
9 | 0018-9545 | 1 |
PageRank | References | Authors |
0.36 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bodong Shang | 1 | 54 | 8.82 |
| Lingjia Liu | 2 | 799 | 92.58 |
| Zhi Tian | 3 | 115 | 14.04 |