Parallel TCP Stream

Parallel TCP streams aim to improve data transfer speeds by concurrently sending data over multiple connections, but optimizing the number of streams is challenging due to network dynamics and resource contention. Current research focuses on developing algorithms, such as reinforcement learning, to dynamically adjust the number of parallel streams, maximizing throughput while ensuring fairness and avoiding network congestion. These advancements are significant for improving the efficiency of data transfer in high-speed networks and have implications for various applications requiring high bandwidth, such as large file transfers and distributed computing.