|
| | | | |
| | | |
| Stat |
Members: 3657
Articles: 2'599'751
Articles rated: 2609
08 October 2024 |
|
| | | | |
|
Article overview
| |
|
|
Federated Learning in Satellite Constellations | | Bho Matthiesen
; Nasrin Razmi
; Israel Leyva-Mayorga
; Armin Dekorsy
; Petar Popovski
; | | Date: |
1 Jun 2022 | | Abstract: | Distributed machine learning (DML) results from the synergy between machine
learning and connectivity. Federated learning (FL) is a prominent instance of
DML in which intermittently connected mobile clients contribute to the training
of a common learning model. This paper presents the new context brought to FL
by satellite constellations where the connectivity patterns are significantly
different from the ones assumed in terrestrial FL. We provide a taxonomy of
different types of satellite connectivity relevant for FL and show how the
distributed training process can overcome the slow convergence due to long
offline times of clients by taking advantage of the predictable intermittency
of the satellite communication links. | | Source: | arXiv, 2206.00307 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
|
| |
|
|
|
REGISTER