A packet processor of a network device repeatedly determines a fill level of a forwarding table that is populated with associations between network addresses and network interfaces of, or coupled to, the network device. The packet processor adjusts, based on the fill level of the forwarding table, a maximum rate according to which the packet processor is permitted to send messages to a central processing unit (CPU) coupled to the packet processor, the messages indicating network addresses that are to be stored in the forwarding table by the CPU. The packet processor of the network device receives packets via network links coupled to the network device; identifies new network addresses of the packets that are not in the forwarding table; and sends messages to the CPU at a rate that does not exceed the maximum rate, the messages indicating the new network addresses are to be added to the forwarding table.

A packet processor of a network device repeatedly determines a fill level of a forwarding table that is populated with associations between network addresses and network interfaces of, or coupled to, the network device. The packet processor adjusts, based on the fill level of the forwarding table, a maximum rate according to which the packet processor is permitted to send messages to a central processing unit (CPU) coupled to the packet processor, the messages indicating network addresses that are to be stored in the forwarding table by the CPU. The packet processor of the network device receives packets via network links coupled to the network device; identifies new network addresses of the packets that are not in the forwarding table; and sends messages to the CPU at a rate that does not exceed the maximum rate, the messages indicating the new network addresses are to be added to the forwarding table.

A rate matching method including: determining a receiving capability of a receive end, where the receiving capability is used to indicate a maximum data processing volume of the receive end in a first transmission time, and/or the receiving capability is used to indicate a maximum data buffer volume of the receive end in a first transmission time; the first transmission time is used to transmit a first transport block to which a first code block belongs; determining N.sub.CB based on the receiving capability, where N.sub.CB represents a code block size used for rate matching; performing rate matching on the first code block based on N.sub.CB. The receive end can adjust, based on a processing capability and/or a buffer capability that are/is of the receive end in a period of time, the code block size used for rate de-matching, to avoid insufficiency in processing capability and/or buffer overflow at the receive end.

A rate matching method including: determining a receiving capability of a receive end, where the receiving capability is used to indicate a maximum data processing volume of the receive end in a first transmission time, and/or the receiving capability is used to indicate a maximum data buffer volume of the receive end in a first transmission time; the first transmission time is used to transmit a first transport block to which a first code block belongs; determining N.sub.CB based on the receiving capability, where N.sub.CB represents a code block size used for rate matching; performing rate matching on the first code block based on N.sub.CB. The receive end can adjust, based on a processing capability and/or a buffer capability that are/is of the receive end in a period of time, the code block size used for rate de-matching, to avoid insufficiency in processing capability and/or buffer overflow at the receive end.

A computer executed process can be configured to identify a network traffic flow of a source network device. The process can select a traffic fidelity rate from a plurality of traffic fidelity rates for sending information regarding the network traffic flow to a digital twin device corresponding to the source network device. The process can transmit the information regarding the network traffic flow to the digital twin device according to the traffic fidelity rate. The digital twin device can be configured to replicate at least one operation of the source network device with respect to the network traffic flow.

A computer executed process can be configured to identify a network traffic flow of a source network device. The process can select a traffic fidelity rate from a plurality of traffic fidelity rates for sending information regarding the network traffic flow to a digital twin device corresponding to the source network device. The process can transmit the information regarding the network traffic flow to the digital twin device according to the traffic fidelity rate. The digital twin device can be configured to replicate at least one operation of the source network device with respect to the network traffic flow.

Certain aspects of the present disclosure provide techniques for wireless communication. The method generally includes determining one or more target metrics associated with a file having a plurality of packets, the plurality of packets comprising at least one of a plurality of uplink packets or a plurality of downlink packets, determining one or more communication parameters for communicating the plurality of packets according to the one or more target metrics associated with the file, and communicating the plurality of packets with a second network entity in accordance with the determined one or more communication parameters.

A network entity for a mobile telecommunications system, including circuitry configured to perform transmission rate control of data transmissions according to a transmission control protocol, wherein the transmission rate control is performed based on an output of a machine learning algorithm including a prediction of a congestion of the data transmissions.

A network entity for a mobile telecommunications system, including circuitry configured to perform transmission rate control of data transmissions according to a transmission control protocol, wherein the transmission rate control is performed based on an output of a machine learning algorithm including a prediction of a congestion of the data transmissions.

Rate limiting systems and methods for regulating access to a shared network resource in a computing device accessed through an application programming interface. A rate limit associated with a shared network resource is assigned to a user for a time period. During the time period, access to the shared network resource is granted or denied repeatedly based upon the rate limit; a cost is calculated using a cost function; and, the rate limit is updated based upon the cost.