FAST TCP is a new congestion control algorithm designed for high-speed, long-latency networks. It addresses four key challenges faced by the current TCP Reno algorithm in such environments. These challenges include slow packet-level window increases, extreme loss probability effects, unavoidable congestion window oscillations, and unstable flow-level dynamics. FAST TCP uses queueing delay as a congestion measure, which provides more accurate information than packet loss probability, enabling better network stability and fairness. The architecture of FAST TCP is modular, allowing separate design and upgrade of its components. It includes data control, window control, and burstiness control. The window control algorithm adjusts the congestion window based on average RTT and queueing delay, leading to improved performance in terms of throughput, fairness, stability, and responsiveness. FAST TCP has been evaluated analytically and experimentally. It achieves the same equilibrium properties as TCP Vegas, including weighted proportional fairness and no penalty for large propagation delays. It is shown to be locally asymptotically stable in single-link networks with heterogeneous flows. Experimental results demonstrate that FAST TCP performs better than Reno, HSTCP, STCP, and BIC TCP in terms of fairness, stability, and responsiveness, especially in dynamic environments with varying delays and traffic patterns. The algorithm uses queueing delay as a congestion measure, which allows for more accurate estimation and better network stability. It also addresses issues related to propagation delay measurement and queueing delay measurement, ensuring fair treatment of flows with different RTTs. FAST TCP can handle heterogeneous protocols and multiple bottlenecks, demonstrating its robustness in complex network scenarios. FAST TCP is a delay-based congestion control algorithm that improves upon TCP Reno by addressing key challenges in high-speed, long-latency networks. It provides better performance in terms of throughput, fairness, stability, and responsiveness, making it a promising solution for future high-speed networks.FAST TCP is a new congestion control algorithm designed for high-speed, long-latency networks. It addresses four key challenges faced by the current TCP Reno algorithm in such environments. These challenges include slow packet-level window increases, extreme loss probability effects, unavoidable congestion window oscillations, and unstable flow-level dynamics. FAST TCP uses queueing delay as a congestion measure, which provides more accurate information than packet loss probability, enabling better network stability and fairness. The architecture of FAST TCP is modular, allowing separate design and upgrade of its components. It includes data control, window control, and burstiness control. The window control algorithm adjusts the congestion window based on average RTT and queueing delay, leading to improved performance in terms of throughput, fairness, stability, and responsiveness. FAST TCP has been evaluated analytically and experimentally. It achieves the same equilibrium properties as TCP Vegas, including weighted proportional fairness and no penalty for large propagation delays. It is shown to be locally asymptotically stable in single-link networks with heterogeneous flows. Experimental results demonstrate that FAST TCP performs better than Reno, HSTCP, STCP, and BIC TCP in terms of fairness, stability, and responsiveness, especially in dynamic environments with varying delays and traffic patterns. The algorithm uses queueing delay as a congestion measure, which allows for more accurate estimation and better network stability. It also addresses issues related to propagation delay measurement and queueing delay measurement, ensuring fair treatment of flows with different RTTs. FAST TCP can handle heterogeneous protocols and multiple bottlenecks, demonstrating its robustness in complex network scenarios. FAST TCP is a delay-based congestion control algorithm that improves upon TCP Reno by addressing key challenges in high-speed, long-latency networks. It provides better performance in terms of throughput, fairness, stability, and responsiveness, making it a promising solution for future high-speed networks.