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Top1. Introduction
FAST TCP (Koo, Choi, & Lee, 2008; Wei, Jin, Low et al., 2006; Li et al., 2016; Zhang & Chen, 2016) was a new network transmission control protocol proposed by Steven H. Low of Network Lab in California institute of technology, which was mainly used for the next generation high performance network with high speed, long delay and large capacity. Based on the balanced design idea of the FAST TCP, the stability, throughput, fairness and fast response were better than TCP Reno, HSTCP and STCP (Wei, Jin, Low et al., 2006; Deng, Chen, & Zhang, 2004). However, the above good performance was assumed that the bottleneck link end had a large enough cache, and adopted tail-drop queue management algorithm (DropTail) (Samreen, 2018). There was no packet loss in the network (Koo, Choi, & Lee, 2008; Wei, Jin, Low et al., 2006; Chen & Chen, 2016; Zhang & Chen, 2016). However, the packet queue cache management (Liu, Zhong, He et al., 2018) of intermediate nodes (such as routers) generally adopted the stochastic early detection active queue management algorithm (Random Early Detection, RED) recommended by RFC2309. According to the average queue length in the cache, RED algorithm will actively drop some packets at a certain probability (Huang, Lin, & Ren, 2006; Tan, Zhang, Peng et al., 2006; Zhang, Tan, & Peng, 2009). By analyzing the code of FAST TCP protocol (CUBINLAB, University of Melbourne, Australia http://www.cubinlab.ee. unimelb.edu.au/ns2fasttcp/), like other network transport protocols, FAST TCP will halve the size of sender window when the source end received three duplicate acknowledgment frames (packet loss). When there was packet loss, the above FAST TCP protocol good performance, especially the stability of the network could not be guaranteed. The reason was that FAST TCP protocol and Reno protocol adopted different window adjustment strategies, so the RED parameter setting guided by TCP Reno/RED stability analysis results based on low-speed network cannot ensure the stability of FAST TCP/RED system in high-speed network (Zhang, Tan, & Peng, 2009; Prakash, Tripathi, Pal et al., 2018).