Name
Title | ||
|---|---|---|
A Deep Reinforcement Learning Approach for Service Migration in MEC-enabled Vehicular Networks |
Abstract | ||
|---|---|---|
Multi-access edge computing (MEC) is a key enabler to reduce the latency of vehicular network. Due to the vehicles mobility, their requested services (e.g., infotainment services) should frequently be migrated across different MEC servers to guarantee their stringent quality of service requirements. In this paper, we study the problem of service migration in a MEC-enabled vehicular network in orde... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/LCN52139.2021.9524882 | 2021 IEEE 46th Conference on Local Computer Networks (LCN) |
Keywords | DocType | ISSN |
Energy consumption,Simulation,Reinforcement learning,Transforms,Quality of service,Markov processes,Servers | Conference | 0742-1303 |
ISBN | Citations | PageRank |
978-1-6654-1886-7 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amine Abouaomar | 1 | 3 | 1.71 |
| Zoubeir Mlika | 2 | 13 | 3.84 |
| Abderrahime Filali | 3 | 1 | 1.36 |
| Soumaya Cherkaoui | 4 | 187 | 40.89 |
| Abdellatif Kobbane | 5 | 126 | 27.54 |