FedHAP: Fast Federated Learning for LEO Constellations using Collaborative HAPs

AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms

“…This ideal setup is rarely available in practice. A most recent approach called FedHAP [2] was proposed which substitutes the traditional GS by one/multiple high altitude platforms (HAPs) floating at 20-30 km above the Earth's surface to act as servers. Although the performance improves, it requires extra hardware.…”

“…Recently, we proposed AsyncFLEO [4], which tackles the model staleness issue and achieves fast convergence within a few hours. However, it still requires HAPs to serve as servers like FedHAP [2]. Different from all the above, FedLEO does not assume ideal setups, violate any FL principle, or introduce any extra hardware (e.g., HAP).…”

“…2 depicts this scheme. On any orbit l, once a visible satellite k receives the global model w t from the GS, the satellite k will send the model to k's neighbors via intraplane ISL 2 , and each of these neighbors will further forward this model to its next-hop neighbor. In the meantime, each satellite on l also starts to train its local copy w t upon receiving it (so there will be multiple concurrent training processes).…”

“…For the first category which this paper focuses on, a massive amount of data such as highresolution images are continuously collected by LEO satellites. Performing data analytics on such big data using AI techniques in order to derive insights and inform decision-makers has huge value and implications, for example in disaster early warning [1] and urban planning [2]. In the traditional school of thought, we can download all these images to a central server such as a ground station (GS), and then train some complex machine learning (ML) models to perform data analytics.…”

“…In the traditional school of thought, we can download all these images to a central server such as a ground station (GS), and then train some complex machine learning (ML) models to perform data analytics. However, this is not desirable in satellite communication (Satcom) because of 1) the network bandwidth limitation [2], 2) the large propagation delay between satellites and the GS [3], 3) the short and irregular visibility period between satellites and the GS [4], and 4) the need for low-latency tracking of space missions [5].…”