In one embodiment, a device obtains path metrics for a network path used to convey application traffic for an online application. The device discretizes the path metrics into labeled states. The device generates state transition visualization data that represents the labeled states as nodes and transitions between the labeled states as edges connecting the nodes. The device provides the state transition visualization data for display.

Described embodiments improve the performance of a computer network via selectively forwarding packets to bypass quality of service (QoS) processing, avoiding processing delays during critical periods of high demand, increasing throughput and efficiency may be increased by sacrificing a small amount of QoS accuracy. QoS processing may be applied to a subset of packets of a flow or connection, referred to herein as “lazy” processing or lazy byte batching. Packets that bypass QoS processing may be immediately forwarded with the same QoS settings as packets of the flow for which QoS processing is applied, resulting in tremendous overhead savings with only minimal decline in accuracy.

Described embodiments improve the performance of a computer network via selectively forwarding packets to bypass quality of service (QoS) processing, avoiding processing delays during critical periods of high demand, increasing throughput and efficiency may be increased by sacrificing a small amount of QoS accuracy. QoS processing may be applied to a subset of packets of a flow or connection, referred to herein as “lazy” processing or lazy byte batching. Packets that bypass QoS processing may be immediately forwarded with the same QoS settings as packets of the flow for which QoS processing is applied, resulting in tremendous overhead savings with only minimal decline in accuracy.

According to one example of the present disclosure, an access point (AP) comprises a wired interface and a wireless interface. External wireless client devices may associate with the AP and the AP may forward traffic received from the wireless clients. The AP includes a virtual client which is to simulate a wireless client device.

A system incorporated in a slice-based network can implement a first virtual infrastructure manager (“VIM”) at a first region. The first VIM can be associated with a first internet protocol (“IP”) prefix range, and configured to receive a second IP prefix range associated with a second region having a second VIM. For compliance with requirements from a software license agreement (“SLA”), the first VIM can monitor a performance of a first virtual network function (“VNF”) of a network slice. In the event of a performance threshold violation, the first VIM can map portions of a workload associated with the violated threshold to the first region and the second region based on respective workload flow data associated with each of the first and second IP prefix ranges. The first VIM can instantiate a second VNF in the region having a workload portion that corresponds to a higher network resource consumption.

System and methods for managing a Wi-Fi network of a plurality of Wi-Fi networks from a cloud-based Network Operations Control (NOC) dashboard are provided. A method, according to one implementations, includes the step of obtaining Wi-Fi metrics and cellular metrics from a network. The method also includes the step of displaying a dashboard on a user interface for use by a support agent at a Network Operations Center (NOC). Also, the method includes the step of displaying both the Wi-Fi metrics and the cellular metrics on the dashboard.

The predictive overlay network architecture of the present invention improves the performance of applications distributing digital content among nodes of an underlying network such as the Internet by establishing and reconfiguring overlay network topologies over which associated content items are distributed. The present invention addresses not only frequently changing network congestion, but also interdependencies among nodes and links of prospective overlay network topologies. The present invention provides a prediction engine that monitors metrics and predicts the relay capacity of individual nodes and links (as well as demand of destination nodes) over time to reflect the extent to which the relaying of content among the nodes of an overlay network will be impacted by (current or future) underlying network congestion. The present invention further provides a topology selector that addresses node and link interdependencies while redistributing excess capacity to determine an overlay network topology that satisfies application-specific performance criteria.

The predictive overlay network architecture of the present invention improves the performance of applications distributing digital content among nodes of an underlying network such as the Internet by establishing and reconfiguring overlay network topologies over which associated content items are distributed. The present invention addresses not only frequently changing network congestion, but also interdependencies among nodes and links of prospective overlay network topologies. The present invention provides a prediction engine that monitors metrics and predicts the relay capacity of individual nodes and links (as well as demand of destination nodes) over time to reflect the extent to which the relaying of content among the nodes of an overlay network will be impacted by (current or future) underlying network congestion. The present invention further provides a topology selector that addresses node and link interdependencies while redistributing excess capacity to determine an overlay network topology that satisfies application-specific performance criteria.

A multi-access edge computing (MEC) platform may receive an indication that a user device has downloaded a MEC application client associated with a MEC application and may send, to the user device, instructions to install a device client. The device client may transmit device information associated with the user device to the MEC platform. The MEC platform may receive the device information associated with the user device and determine, based on the received device information, performance information associated with the MEC application.

In one embodiment, a device obtains a first set of measurements of a path metric for a path in a network that are measured using periodic probing of the path. The device obtains a second set of measurements of the path metric for the path that are measured using fine-grained probing of the path at a higher frequency than that of the periodic probing. The device generates a predictive model that predicts values of the path metric, based on the first set of measurements and on the second set of measurements. The device causes, based on a value of the path metric predicted by the predictive model, traffic to be rerouted from the path to another path in the network.