Joint intelligent optimization of task offloading and service caching for vehicular edge computing
Given the contradiction between limited network resources and massive user demands in Internet of vehicles, an intelligent vehicular edge computing network architecture was proposed to achieve the comprehensive cooperation and intelligent management of network resources.Based on this architecture, a...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2021-01-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021017/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Given the contradiction between limited network resources and massive user demands in Internet of vehicles, an intelligent vehicular edge computing network architecture was proposed to achieve the comprehensive cooperation and intelligent management of network resources.Based on this architecture, a joint optimization scheme of task offloading and service caching was furtherly devised, which formulated an optimization problem about how to offload tasks and allocate computation and cache resources.In view of the dynamics, randomness and time variation of vehicular networks, an asynchronous distributed reinforcement learning algorithm was employed to obtain the optimal task offloading and resource management policy.Simulation results demonstrate that the proposed algorithm achieves significant performance improvement in comparison with the other schemes. |
|---|---|
| ISSN: | 1000-436X |