Various arrangements for increasing a transfer rate of a data transfer via satellite are presented. A satellite gateway may set an accelerated set of communication parameters that control communication between the satellite gateway and the satellite terminal via the satellite and between the satellite gateway and the content source to an accelerated transfer rate between the content source and the satellite terminal. A first set of data may be transferred from the content source to the satellite terminal using the set of communication parameters. After transferring the first set of data, the satellite gateway may adjust the initial set of communication parameters to an adjusted set of communication parameters. The adjusted transfer rate can be lower than the accelerated transfer rate.

Various arrangements for increasing a transfer rate of a data transfer via satellite are presented. A satellite gateway may set an accelerated set of communication parameters that control communication between the satellite gateway and the satellite terminal via the satellite and between the satellite gateway and the content source to an accelerated transfer rate between the content source and the satellite terminal. A first set of data may be transferred from the content source to the satellite terminal using the set of communication parameters. After transferring the first set of data, the satellite gateway may adjust the initial set of communication parameters to an adjusted set of communication parameters. The adjusted transfer rate can be lower than the accelerated transfer rate.

Embodiments of this application disclose a congestion control method and a related device. A Transmission Control Protocol offload engine TOE sends a congestion control notification to a central processing unit CPU, where the congestion control notification instructs the CPU to obtain a target parameter, and the target parameter is used by the CPU to generate a congestion control calculation result. The TOE obtains the congestion control calculation result returned by the CPU, where the congestion control calculation result includes a congestion control window value. The TOE sends a packet based on the congestion control window value. In this application, the TOE and the CPU implement congestion control together. When a new congestion control algorithm emerges, the new congestion control algorithm may be applied without changing a structure of the TOE. Therefore, in this application, an upgrade period of the congestion control algorithm can be shortened, and flexibility can be improved.

Systems and methods provide for Selective Tracking of Acknowledgments (STACKing) to improve buffer utilization and traffic shaping for one or more network devices. A network device can identify a first flow that corresponds to a predetermined traffic class and a predetermined congestion state. The device can determine a current window size and congestion threshold of the first flow. In response to a determination to selectively track a portion of acknowledgments of the first flow, the device can track, in main memory, information of a first portion of acknowledgments of the first flow. The device can exclude, from one or more buffers, a second portion of acknowledgments of the first flow. The device can re-generate and transmit segments corresponding to the second portion of acknowledgments at a target transmission rate based on traffic shaping policies for the predetermined traffic class and congestion state.

Systems and methods provide for Selective Tracking of Acknowledgments (STACKing) to improve buffer utilization and traffic shaping for one or more network devices. A network device can identify a first flow that corresponds to a predetermined traffic class and a predetermined congestion state. The device can determine a current window size and congestion threshold of the first flow. In response to a determination to selectively track a portion of acknowledgments of the first flow, the device can track, in main memory, information of a first portion of acknowledgments of the first flow. The device can exclude, from one or more buffers, a second portion of acknowledgments of the first flow. The device can re-generate and transmit segments corresponding to the second portion of acknowledgments at a target transmission rate based on traffic shaping policies for the predetermined traffic class and congestion state.

Systems and methods provide for generating traffic class-specific congestion signatures and other machine learning models for improving network performance. In some embodiments, a network controller can receive historical traffic data captured by a plurality of network devices within a first period of time that the network devices apply one or more traffic shaping policies for a predetermined traffic class and a predetermined congestion state. The controller can generate training data sets including flows of the historical traffic data labeled as corresponding to the predetermined traffic class and predetermined congestion state. The controller can generate, based on the training data sets, traffic class-specific congestion signatures that receive input traffic data determined to correspond to the predetermined traffic class and output an indication whether the input traffic data corresponds to the predetermined congestion state. The controller can adjust, based on the congestion signatures, traffic shaping operations of the plurality of network devices.

Systems and methods provide for generating traffic class-specific congestion signatures and other machine learning models for improving network performance. In some embodiments, a network controller can receive historical traffic data captured by a plurality of network devices within a first period of time that the network devices apply one or more traffic shaping policies for a predetermined traffic class and a predetermined congestion state. The controller can generate training data sets including flows of the historical traffic data labeled as corresponding to the predetermined traffic class and predetermined congestion state. The controller can generate, based on the training data sets, traffic class-specific congestion signatures that receive input traffic data determined to correspond to the predetermined traffic class and output an indication whether the input traffic data corresponds to the predetermined congestion state. The controller can adjust, based on the congestion signatures, traffic shaping operations of the plurality of network devices.

Aspects of the present disclosure involve systems, methods, computer program products, and the like, for controlling a congestion window (CWND) value of a communication session of a CDN. In particular, a content server may analyze a request to determine or receive an indication of the type of content being requested. The content server may then set the initial CWND based on the type of content being requested. For example, the content server may set a relatively high CWND value for requested content that is not particularly large, such as image files or text, so that the data of the content is received at the client device quickly. For larger files or files that a have a determined smaller urgency, the initial CWND may be set at a lower value to ensure that providing the data of the content does not congest the link between the devices.

Aspects of the present disclosure involve systems, methods, computer program products, and the like, for controlling a congestion window (CWND) value of a communication session of a CDN. In particular, a content server may analyze a request to determine or receive an indication of the type of content being requested. The content server may then set the initial CWND based on the type of content being requested. For example, the content server may set a relatively high CWND value for requested content that is not particularly large, such as image files or text, so that the data of the content is received at the client device quickly. For larger files or files that a have a determined smaller urgency, the initial CWND may be set at a lower value to ensure that providing the data of the content does not congest the link between the devices.

Systems and methods for controlling congestion of a data network are provided. An engine round-trip time (RTT) and a fabric RTT for a network flow are determined. An engine-based congestion window size for the flow is determined based on the engine RTT and a target engine RTT. A fabric-based congestion window size for the flow is determined based on the fabric RTT and a target fabric RTT. The smaller of the engine-based congestion window size and the fabric-based window size is selected for use in transmitting a future packet associated with the flow. The target engine RTT is determined based in part on the current congestion window used to transmit packets for the flow and/or the target fabric RTT is determined based on a number of hops packets associated with the flow traverse from a source to a destination associated with the flow.