A communication method is provided. A first network element receives an association identifier of a first application from a session management network element, where the association identifier is for associating different quality of service QoS flows of the first application. The first network element performs joint scheduling on the plurality of QoS flows of the first application that each carry the association identifier. Based on this solution, the first network element can identify, based on the association identifier, QoS flows belonging to a same application, and perform joint scheduling, and it is ensured that the QoS flows of the same application can arrive at a terminal device simultaneously or a time interval between arrivals at the terminal device is small, so that service experience of a user can be improved.

In a wireless network, a user equipment (UE) may support reflective quality of service (QoS), where QoS applied to uplink packets is implicitly derived from downlink packets. For example, when the UE receives a downlink packet that includes a reflective QoS (RQoS) indicator and a QoS flow identifier (QFI), the UE may apply the same QoS associated with the downlink packet to an uplink packet with one or more attributes that match the downlink packet. However, for a received downlink encapsulating security payload (ESP) packet that includes an RQoS indicator and a QFI, a modem cannot determine an uplink security parameters index (SPI) and downlink SPI pairing needed to enable RQoS because the uplink/downlink SPI pairing is known only by the upper layer. Accordingly, some aspects described herein enable the modem to learn uplink/downlink SPI pairings for ESP packets and thereby enable RQoS for ESP packets.

In a wireless network, a user equipment (UE) may support reflective quality of service (QoS), where QoS applied to uplink packets is implicitly derived from downlink packets. For example, when the UE receives a downlink packet that includes a reflective QoS (RQoS) indicator and a QoS flow identifier (QFI), the UE may apply the same QoS associated with the downlink packet to an uplink packet with one or more attributes that match the downlink packet. However, for a received downlink encapsulating security payload (ESP) packet that includes an RQoS indicator and a QFI, a modem cannot determine an uplink security parameters index (SPI) and downlink SPI pairing needed to enable RQoS because the uplink/downlink SPI pairing is known only by the upper layer. Accordingly, some aspects described herein enable the modem to learn uplink/downlink SPI pairings for ESP packets and thereby enable RQoS for ESP packets.

A technique involves modular storage of network service plan components and provisioning of same. A subset of the capabilities of a service design system can be granted to a sandbox system to enable customization of service plan offerings or other controls.

Secure device data records (DDRs) are provided. In some embodiments, a system for secure DDRs includes a processor of a wireless communication device for wireless communication with a wireless network, in which the processor is configured with a secure execution environment, and in which the secure execution environment is configured to: monitor service usage of the wireless communication device with the wireless network; and generate a plurality of device data records of the monitored service usage of the wireless communication device with the wireless network, in which each device data record is associated with a unique sequence order identifier; and a memory coupled to the processor and configured to provide the processor with instructions. In some embodiments, the secure execution environment is located in an application processor, in a modem processor, and/or in a subscriber identity module (SIM).

Aspects of the present disclosure include a content delivery network (CDN) for delivering content associated with a plurality of different types of applications/devices. Using a CDN flow application, a plurality of network flow parameters are generated for content delivery unique to different types of applications or devices. The network flow parameters include customized data transmission rates. The network flow parameters include predetermined settings for transmission control protocol (TCP) connections between the CDN and devices using a TCP flow control mechanism. Upon receiving a content request, the CDN fulfills the content request based upon first network flow parameters. The network flow parameters may be adjusted for each of the plurality of different types of applications/devices. The network flow parameters may be generated based upon requests or based upon the performance of each of the plurality of applications/devices.

Aspects of the present disclosure include a content delivery network (CDN) for delivering content associated with a plurality of different types of applications/devices. Using a CDN flow application, a plurality of network flow parameters are generated for content delivery unique to different types of applications or devices. The network flow parameters include customized data transmission rates. The network flow parameters include predetermined settings for transmission control protocol (TCP) connections between the CDN and devices using a TCP flow control mechanism. Upon receiving a content request, the CDN fulfills the content request based upon first network flow parameters. The network flow parameters may be adjusted for each of the plurality of different types of applications/devices. The network flow parameters may be generated based upon requests or based upon the performance of each of the plurality of applications/devices.

In one embodiment, a networking device in a network detects an traffic flow conveyed in the network via the networking device. The networking device generates flow data for the traffic flow. The networking device performs a classification of the traffic flow using the flow data as input to a machine learning-based classifier. The networking device performs a mediation action based on the classification of the traffic flow.

In one embodiment, a networking device in a network detects an traffic flow conveyed in the network via the networking device. The networking device generates flow data for the traffic flow. The networking device performs a classification of the traffic flow using the flow data as input to a machine learning-based classifier. The networking device performs a mediation action based on the classification of the traffic flow.

Example network devices, systems, and methods are disclosed. In an example, a network device includes memory configured to store information associated with one or more service level agreements (SLAs) for applications in a software-defined wide area network (SD-WAN) and an application-based multipath routing (AMR) module including processing circuitry. The AMR module is configured to identify, based on criteria, one or more of the applications for AMR, wherein each criterion of the criteria is associated with a corresponding property of an application. The AMR module is configured to determine a breach of one of the SLAs on each WAN link associated with a first application of the identified one or more applications. The AMR module is configured to apply, in response to determining the breach, AMR for the first application.