Examples described herein relate to media transmission. In some examples, based on increased available bandwidth to transmit media data to a receiver device and based on unavailability of media data, fill data can be into a network data buffer for transmission in one or more packets. In some examples, based on increased available bandwidth to transmit media data to a receiver device and based on availability of media data, media data can be provided into the network data buffer for transmission to the receiver device.

A queue scheduling method, apparatus, and system are provided, to flexibly manage a queue, meet an actual transmission requirement, and reduce resources. The queue scheduling method implemented by a processing apparatus includes: generating an HQoS scheduling tree including a plurality of leaf nodes, each of which identifies a queue on a traffic management (TM) hardware entity including a plurality of queues; obtaining traffic characteristics of the plurality of queues based on the plurality of leaf nodes; determining a scheduling parameter of at least one queue in the plurality of queues based on the traffic characteristics which are of data flows transmitted by the plurality of queues; sending to a scheduling apparatus a scheduling message corresponding to the at least one queue in the TM hardware entity, including the scheduling parameter of the at least one queue used to schedule the at least one queue.

A queue scheduling method, apparatus, and system are provided, to flexibly manage a queue, meet an actual transmission requirement, and reduce resources. The queue scheduling method implemented by a processing apparatus includes: generating an HQoS scheduling tree including a plurality of leaf nodes, each of which identifies a queue on a traffic management (TM) hardware entity including a plurality of queues; obtaining traffic characteristics of the plurality of queues based on the plurality of leaf nodes; determining a scheduling parameter of at least one queue in the plurality of queues based on the traffic characteristics which are of data flows transmitted by the plurality of queues; sending to a scheduling apparatus a scheduling message corresponding to the at least one queue in the TM hardware entity, including the scheduling parameter of the at least one queue used to schedule the at least one queue.

Systems and methods are provided for measuring available bandwidth available in a black box network by determining a probing rate of packet transmissions between a sender and receiver. The optimal probing rate and bandwidth estimate may be determined. Additional actions may be performed, like automatically rerouting packets and/or load balancing network traffic after the probing rate is determined.

This application provides a packet scheduling method and a related device. The method includes: An access device receives a to-be-scheduled packet, and obtains an actual packet length of the to-be-scheduled packet; the access device determines a first compensation value and a second compensation value based on the to-be-scheduled packet, and determines a first packet length and a second packet length; and the access device schedules the to-be-scheduled packet based on the first packet length and the second packet length. By implementing the method in this application, the access device estimates a packet length of a packet received by each device on a packet forwarding path, and then schedules the packet based on the estimated packet length of the packet received by each device, so that the access device can manage bandwidth of each device on a network more accurately.

This application provides a packet scheduling method and a related device. The method includes: An access device receives a to-be-scheduled packet, and obtains an actual packet length of the to-be-scheduled packet; the access device determines a first compensation value and a second compensation value based on the to-be-scheduled packet, and determines a first packet length and a second packet length; and the access device schedules the to-be-scheduled packet based on the first packet length and the second packet length. By implementing the method in this application, the access device estimates a packet length of a packet received by each device on a packet forwarding path, and then schedules the packet based on the estimated packet length of the packet received by each device, so that the access device can manage bandwidth of each device on a network more accurately.

A method for submitting a training task by a rate limiting queue includes: monitoring load state information and predicting, by a trained neural network prediction model, a token bucket rate limiting queue parameter according to the load state information; adjusting the bearing capacity of a token bucket rate limiting queue according to the token bucket rate limiting queue parameter; configuring task parameters of training tasks, and determining, according to the task parameters and the bearing capacity, whether the token bucket rate limiting queue has the sufficient residual space to place the training tasks; in response to determining that the token bucket rate limiting queue has the sufficient residual space to place the training tasks, sending the training tasks to the token bucket rate limiting queue; and sequentially submitting the training tasks according to the bearing capacity in chronological order of the training tasks entering the token bucket rate limiting queue.

A method for submitting a training task by a rate limiting queue includes: monitoring load state information and predicting, by a trained neural network prediction model, a token bucket rate limiting queue parameter according to the load state information; adjusting the bearing capacity of a token bucket rate limiting queue according to the token bucket rate limiting queue parameter; configuring task parameters of training tasks, and determining, according to the task parameters and the bearing capacity, whether the token bucket rate limiting queue has the sufficient residual space to place the training tasks; in response to determining that the token bucket rate limiting queue has the sufficient residual space to place the training tasks, sending the training tasks to the token bucket rate limiting queue; and sequentially submitting the training tasks according to the bearing capacity in chronological order of the training tasks entering the token bucket rate limiting queue.

Systems and methods are provided for a new type of quality of service (QoS) primitive at a network device that has better performance than traditional QoS primitives. The QoS primitive may comprise a token bucket with active queue management (TBAQM). Particularly, the TBAQM may receive a data packet that is processed by the token bucket; adjust tokens associated with the token bucket, where the tokens are added based on a configured rate and subtracted in association with processing the data packet; determine a number of tokens associated with the token bucket, comprising: when the token bucket has zero tokens, initiating a first action with the data packet, and when the token bucket has more than zero tokens, determining a marking probability based on the number of tokens and initiating a second action based on the marking probability.

Systems and methods are provided for a new type of quality of service (QoS) primitive at a network device that has better performance than traditional QoS primitives. The QoS primitive may comprise a token bucket with active queue management (TBAQM). Particularly, the TBAQM may receive a data packet that is processed by the token bucket; adjust tokens associated with the token bucket, where the tokens are added based on a configured rate and subtracted in association with processing the data packet; determine a number of tokens associated with the token bucket, comprising: when the token bucket has zero tokens, initiating a first action with the data packet, and when the token bucket has more than zero tokens, determining a marking probability based on the number of tokens and initiating a second action based on the marking probability.