Name
Title | ||
|---|---|---|
Multi-Agent Multi-Armed Bandit Learning for Online Management of Edge-Assisted Computing |
Abstract | ||
|---|---|---|
By orchestrating resources of edge and core network, the delays of edge-assisted computing can decrease. Offloading scheduling is challenging though, especially in the presence of many edge devices with randomly varying link and computing conditions. This paper presents a new online learning-based approach to the offloading scheduling, where multi-agent multi-armed bandit (MA-MAB) learning is desi... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCOMM.2021.3113386 | IEEE Transactions on Communications |
Keywords | DocType | Volume |
Task analysis,Delays,Servers,Program processors,Costs,Edge computing,Computational modeling | Journal | 69 |
Issue | ISSN | Citations |
12 | 0090-6778 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bochun Wu | 1 | 1 | 1.36 |
| Tianyi Chen | 2 | 43 | 7.52 |
| Wei Ni | 3 | 474 | 70.16 |
| Xin Wang | 4 | 1169 | 111.70 |