Network congestion control algorithms are the key factor indetermining network transport performance. In recent years, the spreading network, the growing network bandwidth, and the increasing user requirements for network performance have brought challenges to the design of congestion control algorithms. To adapt to different network environments, many novel design ideas of congestion control algorithms have been proposed recently, which have greatly improved the performance of networks and user experience. This study reviews innovative congestion control algorithm design ideas and classifies them into four major categories: reservation scheduling, direct measurement, machine learning-based learning, and iterative detection. It introduces the corresponding representative congestion control algorithms, and further compares and analyzes the advantages and disadvantages of various congestion control ideas and methods. Finally, the study looks forward to future development direction on congestion control to inspire research in this field.