Fedsn: A federated learning framework over heterogeneous leo satellite networks
Recently, a large number of Low Earth Orbit (LEO) satellites have been launched and
deployed successfully in space. Due to multimodal sensors equipped by the LEO satellites …
deployed successfully in space. Due to multimodal sensors equipped by the LEO satellites …
Satellite computing: Vision and challenges
The space industry experiences a rise in low-Earth-orbit satellite mega-constellations to
achieve universal connectivity. At the same time, cloud firms (such as Google, Microsoft, and …
achieve universal connectivity. At the same time, cloud firms (such as Google, Microsoft, and …
Federated split learning for sequential data in satellite–terrestrial integrated networks
W Jiang, H Han, Y Zhang, J Mu - Information Fusion, 2024 - Elsevier
Satellite–terrestrial integrated networks (STINs) have been proposed for B5G/6G mobile
communication, and the increase in the computation and communication capacities of …
communication, and the increase in the computation and communication capacities of …
Autofed: Heterogeneity-aware federated multimodal learning for robust autonomous driving
Object detection with on-board sensors (eg, lidar, radar, and camera) is crucial to
autonomous driving (AD), and these sensors complement each other in modalities. While …
autonomous driving (AD), and these sensors complement each other in modalities. While …
Fedsn: A general federated learning framework over leo satellite networks
Recently, a large number of Low Earth Orbit (LEO) satellites have been launched and
deployed successfully in space by commercial companies, such as SpaceX. Due to …
deployed successfully in space by commercial companies, such as SpaceX. Due to …
Fedfusion: Manifold driven federated learning for multi-satellite and multi-modality fusion
Multi-Satellite, multi-modality in-orbit fusion is a challenging task as it explores the fusion
representation of complex high-dimensional data under limited computational resources …
representation of complex high-dimensional data under limited computational resources …
On-board federated learning for satellite clusters with inter-satellite links
The emergence of mega-constellations of interconnected satellites has a major impact on
the integration of cellular wireless and non-terrestrial networks, while simultaneously …
the integration of cellular wireless and non-terrestrial networks, while simultaneously …
FedLEO: An offloading-assisted decentralized federated learning framework for low earth orbit satellite networks
Low Earth orbit (LEO) satellites enable complex Earth observation tasks (eg, remote sensing
and cooperative monitoring) by leveraging large-scale satellite-generated Earth imageries …
and cooperative monitoring) by leveraging large-scale satellite-generated Earth imageries …
A comprehensive survey on orbital edge computing: Systems, applications, and algorithms
The number of satellites, especially those operating in low-earth orbit (LEO), is exploding in
recent years. Additionally, the use of COTS hardware into those satellites enables a new …
recent years. Additionally, the use of COTS hardware into those satellites enables a new …
AsyncFLEO: Asynchronous federated learning for LEO satellite constellations with high-altitude platforms
Low Earth Orbit (LEO) constellations, each comprising a large number of satellites, have
become a new source of big data" from the sky". Downloading such data to a ground station …
become a new source of big data" from the sky". Downloading such data to a ground station …