In a multilink system, block acknowledgment is performed at TID level. It is commonly accepted that acknowledgment policy refrains low latency delivery. However, it is often that traffic streams combine low-latency data and data requiring a high level of reliability. A need exists to facilitate the transmission of low-latency data units of a TID when a multilink operation, such as in 802.11be, is implemented with an acknowledgment policy. One specific link from amongst the multiple links may be dedicated to low latency data for which the originator and the recipient no longer take into account the acknowledgment. It turns that the originator can remove the low latency data from its transmit buffer immediately after transmission, while the recipient can deliver these data to the upper layer without waiting for the good reception of all preceding data, according to a sequence numbering. Low-latency services are consequently improved.

Systems and methods described herein provide an intelligent MEC resource scheduling service. A network device in a MEC network stores, in a memory, threshold values indicating overload conditions for resource usage by a first MEC cluster; monitors resource usage in the first MEC cluster; determines, based on the monitoring, when one of the threshold values is reached; identifies available resources in a second MEC cluster; and re-directs, based on the identifying, at least some of the resource usage from the first MEC cluster to the second MEC cluster.

The present application relates to devices and components including apparatuses, systems, and methods for technologies for offloading paths from edge computing resources.

Methods and apparatuses are presented to facilitate coexistence between multiple wireless communication protocols implemented by a wireless communication device, by dynamically adjusting priority between the two protocols. The wireless communication device may typically favor a first protocol (e.g. Bluetooth/BTLE), prioritizing resource requests by the first protocol. In certain use cases, the first protocol may demand high resource usage for an extended time, particularly for newer tracking and wearable devices, such as location tags, watches, headsets, etc. Such applications can disrupt existing use cases for a second protocol (e.g., Wi-Fi). Therefore, the wireless communication device may dynamically determine whether the second protocol is performing critical operations, such as latency-sensitive applications or high-performance operations. If so, the wireless communication device may allocate resources accordingly in real time, e.g., by reducing or limiting the resources assigned to the first protocol, to allow increased resources for the second protocol.

A fifth-generation core network (5GC) provides 5G radio access network (RAN) services to a user equipment (UE) in a time-sensitive communications (TSC) network (TSN). This includes receiving a protocol data unit (PDU) session establishment request from the UE, the PDU session establishment request including an industrial Internet of Things (IIoT) vertical or application type, identifying a TSN application function (AF) relating to the IIoT vertical or application type, determining quality of service (QoS) parameters for communications between the UE and the 5G RAN based on the identified TSN AF, the QoS parameters including a survival time for the IIoT vertical or application type and establishing a PDU session with the UE when the QoS parameters including the survival time are satisfied.

Various embodiments comprise systems, methods, architectures, mechanisms and apparatus managing UE handovers between MNO and MVNO networks by using pre-emptive signaling between the two networks so as to coordinate UE session migration between the two networks, such as for UE having dual SIM capability and a software agent functioning as a connection manager is configured to reduce handover delay by maintaining an active profile of active applications, such as via a snapshot module configured to keep track of active packet flows for each application by, illustratively, tracking such application packet flows at the packet level and maintaining a corresponding snapshot of current application packet flows.

Techniques for distributed computation are provided. A plurality of edge computing devices available to execute a computing task for a client device is identified, and a first latency of transmitting data among the plurality of edge computing devices is determined. A second latency of transmitting data from the client device to the plurality of edge computing devices is determined, and a set of edge computing devices, from the plurality of edge computing devices, is determined to execute the computing task based at least in part on the first and second latencies. Execution of the computing task is facilitated using the set of edge computing devices, where the client device transmits a portion of the computing task directly to each edge computing device of the set of edge computing devices.

A latency manager at a base station in a radio access network (RAN) can be configured to dynamically determine an end-to-end latency associated with an end-to-end connection for a UE that extends through the RAN, a transport network, and a core network. The latency manager can also dynamically determine whether the end-to-end latency meets an end-to-end latency goal associated with the end-to-end connection. If the end-to-end latency does not meet the end-to-end latency goal, the latency manager can cause the base station to dynamically adjust radio resources to lower a RAN latency associated with the end-to-end connection. Lowering the RAN latency can cause the overall end-to-end latency to be lowered and to meet the end-to-end latency goal. In some examples, the latency manager may also request that the transport network and/or the core network take actions to reduce latencies to reduce the end-to-end latency to meet the end-to-end latency goal.

The technologies described herein are generally directed to improving operation of networked applications where consistency of delays can improve performance in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include identifying network node equipment executing an online application via a communication link to application server equipment. The method can further include evaluating delays associated with the communication link over time, e.g., based on delay information. Further, the method can include, based on the evaluating, adjusting a consistency of the delays.

A network device obtains service requirements associated with a customer identifier, obtains a first profile describing an infrastructure design of multiple transport domains associated with at least one network slice of a network, and obtains a second profile describing performance characteristics of the multiple transport domains of the at least one network slice. The network device receives training data associated with performance measurements of the multiple transport domains of the at least one network slice, and updates a machine learning model based on the training data. The network device selects at least one of the multiple transport domains for orchestration using the updated machine learning model, the service requirements, the first profile, and the second profile.