Fountain code-based multipath reliable transmission scheme with RNN-assisted predictive feedback

With the rapid advancement of internet technology, the demand for network performance continues to grow. Due to the problems of low fault tolerance and limited available bandwidth of traditional single-path transmission methods, multipath transmission has received widespread attention. However, existing multipath transmission schemes may encounter problems such as packet disorder and mutual interference between paths when facing complex network environments, thus reducing network transmission efficiency. This paper proposes a multipath reliable transmission scheme (FC-MPRT) based on fountain codes and recurrent neural networks (RNNs) to address these challenges. The scheme fully leverages the randomness and reliability of fountain codes to effectively solve the buffer-blocking problem caused by frequent packet loss retransmissions and the requirement for packets to arrive in order. Additionally, a supervised prediction scheme based on RNN is designed at the data receiving end to mitigate the potential resource wastage problem during encoding and decoding. The transmission efficiency is significantly enhanced by predicting the arrival of packets. We evaluate the performance of FC-MPRT in various network scenarios on NS-3 and Mininet platforms. Simulation results demonstrate that FC-MPRT achieves a 66.1% improvement in throughput and a 47.6% reduction in the average block transmission delay compared to existing multipath transmission schemes.