A real-time dynamic API traffic shaping and infrastructure resource protection in a multiclient network environment is provided. A traffic rules engine (TRE) applies traffic shaping only to customers that are utilizing “more than their fair share” of the currently available bandwidth without allowing them to negatively impact the user experience of other users. The present invention takes current API traffic into consideration, allowing one or a few high volume users to utilize most of all available bandwidth as long as other users do not need that bandwidth. This includes dynamically measuring and adjusting which users had traffic shaping applied to them based on the overall traffic during any given second. The solution of the present invention avoids any slowdown of customer API requests unless the maximum allowable TPS limit is near to being reached.

Disclosed herein are various embodiments to prevent, detect, or take action in response to the moving a device credential from one device to another, the improper configuration of a service processor, a missing service processor, or the tampering with a service processor in device-assisted services (DAS) systems.

This application provides a packet transmission method, apparatus, and system, and relates to the field of network technologies. The method is applied to a network architecture including a user terminal, a first forwarding device and a second forwarding device. A tunnel is disposed between the first forwarding device and the second forwarding device. The method includes: The first forwarding device receives packets forwarded by the user terminal in the load balancing mode, where the packets include a keepalive packet, and the first forwarding device is a standby forwarding device corresponding to the user terminal. The first forwarding device forwards the keepalive packet to the second forwarding device through the tunnel, where the second forwarding device is an active forwarding device corresponding to the user terminal.

This application provides a packet transmission method, apparatus, and system, and relates to the field of network technologies. The method is applied to a network architecture including a user terminal, a first forwarding device and a second forwarding device. A tunnel is disposed between the first forwarding device and the second forwarding device. The method includes: The first forwarding device receives packets forwarded by the user terminal in the load balancing mode, where the packets include a keepalive packet, and the first forwarding device is a standby forwarding device corresponding to the user terminal. The first forwarding device forwards the keepalive packet to the second forwarding device through the tunnel, where the second forwarding device is an active forwarding device corresponding to the user terminal.

The disclosure provides a method and a device for efficiently operating network slicing. According to the disclosure, a method of operating a first node configured to manage a network slice of a communication system includes: transmitting a service level agreement (SLA) range for each network slice subnet and a message requesting a resource according to the SLA range to a second node configured to manage the network slice subnet, receiving SLA arrangement flavor mapping relationship information in the network slice subnet unit from the second node, and identifying the SLA arrangement flavor mapping relationship in a network slice unit based on the received SLA arrangement flavor mapping relationship information in a network slice subnet unit.

The disclosure provides a method and a device for efficiently operating network slicing. According to the disclosure, a method of operating a first node configured to manage a network slice of a communication system includes: transmitting a service level agreement (SLA) range for each network slice subnet and a message requesting a resource according to the SLA range to a second node configured to manage the network slice subnet, receiving SLA arrangement flavor mapping relationship information in the network slice subnet unit from the second node, and identifying the SLA arrangement flavor mapping relationship in a network slice unit based on the received SLA arrangement flavor mapping relationship information in a network slice subnet unit.

A data processing method and apparatus are disclosed. The data processing method includes: receiving, by a first edge computing node in an edge computing cluster, a container image update instruction; obtaining, by the first edge computing node, a to-be-updated container image; and sending, by the first edge computing node, the to-be-updated container image to another edge computing node in the edge computing cluster. The first edge computing node is an edge computing node in the edge computing cluster, the edge computing cluster includes at least two edge computing nodes, and the container image update instruction is used to instruct the at least two edge computing nodes in the edge computing cluster to update a container image. In this way, the time required for downloading the container image is reduced.

A data processing method and apparatus are disclosed. The data processing method includes: receiving, by a first edge computing node in an edge computing cluster, a container image update instruction; obtaining, by the first edge computing node, a to-be-updated container image; and sending, by the first edge computing node, the to-be-updated container image to another edge computing node in the edge computing cluster. The first edge computing node is an edge computing node in the edge computing cluster, the edge computing cluster includes at least two edge computing nodes, and the container image update instruction is used to instruct the at least two edge computing nodes in the edge computing cluster to update a container image. In this way, the time required for downloading the container image is reduced.

A computer-implemented method upgrades an edge network based on analysis by a learning model. The method includes identifying, in a network, a plurality of devices, where each device in the network is configured to provide data on at least one other device in the network. The method also includes determining capabilities of each device of the plurality of devices. The method further includes monitoring, for each device, capacity information and tasks performed during operation of the network. The method includes analyzing, based on the monitoring, each use of each device. The method also includes recommending, in response to the analyzing and by a learning model, a first upgrade to the network. The method further includes implementing the first upgrade.

A computer-implemented method upgrades an edge network based on analysis by a learning model. The method includes identifying, in a network, a plurality of devices, where each device in the network is configured to provide data on at least one other device in the network. The method also includes determining capabilities of each device of the plurality of devices. The method further includes monitoring, for each device, capacity information and tasks performed during operation of the network. The method includes analyzing, based on the monitoring, each use of each device. The method also includes recommending, in response to the analyzing and by a learning model, a first upgrade to the network. The method further includes implementing the first upgrade.