The invention discloses a P2P (Peer-to-Peer)-based efficient extensible
federated learning system construction method, equipment and a product. Firstly, a parameter
server selects a
client based on statistical efficiency,
processing speed, distribution contribution and other historical information, and a
client distributor assigns a special
actuator to the selected
client. The
actuator operates in an isolated container environment, carries out real communication through a special network card, and distributes a
global model by using a P2P communication
library; the
actuator sends the training configuration, the local
data set and the
global model to the computing node, and the computing node performs a plurality of rounds of local training and then returns model update to the actuator; the parameter
server receives a model update of the actuator and generates a new
global model. According to the method, model distribution is optimized through P2P communication, and a client selection scheme comprehensively considering various historical information is designed. In addition, the FedP2P constructs a high-fidelity
simulation platform to accurately simulate calculation and communication behaviors in actual federation training, and then the effectiveness of scheme design is verified.