## 2 Related Work  
In traditional schemes, the sending node mainly handles transmission rate control. The authors of [1] proposed Reno, and the authors of [2] proposed NewReno. These classic TCP congestion control algorithms use packet loss events as signals of network congestion. After detecting packet loss, the sending node uses the additive increase multiplicative decrease (AIMD) mechanism to reduce the congestion window and reduce the transmission rate sharply. However, when the network is not congested, packet loss may also occur, and reducing the transmission rate will result in a loss of throughput performance. The authors of [3] proposed the CUBIC algorithm to solve this problem. When the window grows, CUBIC uses a cubic function of the time since the last packet loss to achieve high performance, making it the default congestion control algorithm in Linux systems. The authors of [4] proposed the first method to use delay as a congestion signal, called TCP Vegas. The authors of [5] combined the advantages of packet loss-based and delay-based methods to design Compound TCP. The authors of [6] developed a new method called BBR. BBR will periodically increase and decrease the transmission rate in an attempt to detect larger bandwidths while emptying the queued packets in the network node queue to measure the minimum round-trip time (RTT). This method achieves optimal performance by estimating the RTT and bottleneck bandwidth, keeping the congestion window equal to the bandwidth-delay product (BDP). The authors of [7] developed the Multipath TCP (MPTCP) protocol, which allows a single data stream of TCP to be divided into multiple subflows, and each subflow can choose different paths for data transmission [8; 9; 10]. However, when various subflows of an MPTCP stream are routed and assigned to a common bottleneck link (shared bottleneck) [11; 12], they will occupy more bandwidth than regular single-path TCP streams. The authors of [13] designed a coupling COUPLED algorithm similar to Reno window adjustment. When a subflow encounters congestion, the transmission of that path is immediately cut off, and the total window sum of all subflows is halved. This algorithm is based on the assumption that all subflows have equal RTTs. The authors of [14] proposed a SEMI-COUPLED algorithm to improve the COUPLED algorithm. When a subflow encounters congestion, the SEMI-COUPLED algorithm reduces the sending window of the subflow by half to replace the cutoff of congested subflow transmission in the COUPLED algorithm. The authors of [15] further improved the SEMI-COUPLED algorithm. It is proposed that the LIA algorithm solves the problem of fairness from the perspective of load balancing between subflows, which cannot be guaranteed between subflows with different RTTs. To fundamentally address the demand for content distribution, researchers have proposed an ICN that completely changes the existing network architecture, including different solutions such as CCNs [16], NDNs [17], and SEANET [18]. Under this new network architecture, the receiving node is responsible for congestion control. The authors of [19] proposed an ICP algorithm using a mechanism similar to TCP's AIMD window adjustment method. The congestion window of the ICP algorithm increases the size of a data packet by one for every successful transmission of data with a congestion window size and becomes A (0 < A < 1) times the original length when congestion occurs. The authors of [20] also adopted a TCP-like congestion window adjustment algorithm to design the ICTP algorithm. In addition, the ICTP algorithm also considers the trade-off between traffic control, security, and overhead caused by the size of data blocks. The authors of [21] designed the BBR-CD method to apply the BBR algorithm to an ICN. It improved the estimation of the RTT, such as through using the average RTT instead of the minimum RTT and using filters to remove noise from RTT samples. Some studies involve network nodes in transmission rate control.