In the present disclosure, a network monitoring system is provided including an IP network monitoring unit (610) that monitors an IP network to which an IP device is connected; and a non-IP device monitoring unit (630) that monitors a non-IP device. It is possible to monitor both the IP network and the non-IP device in a system that includes the IP network including the IP device and the non-IP device.

A computer system receives a data stream with a plurality of packets. In response to receiving the data stream with the plurality of packets, the computer system distributes individual packets of the plurality of packets to the inputs of each of a plurality of processing nodes. Each respective processing node has a local queue storing a respective number of packets to be processed by the respective processing node. Distributing a respective packet of the plurality of packets to the inputs of each of the plurality of processing nodes includes delaying sending the respective packet to each of the plurality of processing nodes by a delay time that is a non-linear function of an average number of packets in the local queues of the respective processing nodes.

A computer system receives a data stream with a plurality of packets. In response to receiving the data stream with the plurality of packets, the computer system distributes individual packets of the plurality of packets to the inputs of each of a plurality of processing nodes. Each respective processing node has a local queue storing a respective number of packets to be processed by the respective processing node. Distributing a respective packet of the plurality of packets to the inputs of each of the plurality of processing nodes includes delaying sending the respective packet to each of the plurality of processing nodes by a delay time that is a non-linear function of an average number of packets in the local queues of the respective processing nodes.

In one embodiment, a label stability analyzer service receives classification data indicative of device type labels assigned to endpoints in a network by a device classification service. The label stability analyzer service counts device type label changes made by the device classification service to the endpoints. The label stability analyzer service computes variability metrics for the device type labels, wherein the variability metric for a device type label is based on a count of the device type label changes associated with that label. The label stability analyzer service determines, based on one of the variability metrics for a particular one of the device type labels exceeding a threshold value, a configuration change for the device classification service that adjusts how the device classification service applies the particular label to endpoints. The label stability analyzer service provides the configuration change to the device classification service.

In one embodiment, a label stability analyzer service receives classification data indicative of device type labels assigned to endpoints in a network by a device classification service. The label stability analyzer service counts device type label changes made by the device classification service to the endpoints. The label stability analyzer service computes variability metrics for the device type labels, wherein the variability metric for a device type label is based on a count of the device type label changes associated with that label. The label stability analyzer service determines, based on one of the variability metrics for a particular one of the device type labels exceeding a threshold value, a configuration change for the device classification service that adjusts how the device classification service applies the particular label to endpoints. The label stability analyzer service provides the configuration change to the device classification service.

An apparatus and method for a power-efficient framework to maintain data synchronization of a mobile personal computer (MPC) are described. In one embodiment, the method includes the detection of a data synchronization wakeup event while the MPC is operating according to a sleep state. Subsequent to wakeup event, at least one system resource is disabled to provide a minimum number of system resources required to re-establish a network connection. In one embodiment, user data from a network server is synchronized on the MPC without user intervention; the mobile platform system resumes operation according to the sleep state. In one embodiment, a wakeup alarm is programmed according to a user history profile regarding received e-mails. In a further embodiment, data synchronizing involves disabling a display, and throttling the system processor to operate at a reduced frequency. Other embodiments are described and claimed.

An apparatus and method for a power-efficient framework to maintain data synchronization of a mobile personal computer (MPC) are described. In one embodiment, the method includes the detection of a data synchronization wakeup event while the MPC is operating according to a sleep state. Subsequent to wakeup event, at least one system resource is disabled to provide a minimum number of system resources required to re-establish a network connection. In one embodiment, user data from a network server is synchronized on the MPC without user intervention; the mobile platform system resumes operation according to the sleep state. In one embodiment, a wakeup alarm is programmed according to a user history profile regarding received e-mails. In a further embodiment, data synchronizing involves disabling a display, and throttling the system processor to operate at a reduced frequency. Other embodiments are described and claimed.

Some embodiments of the invention provide a method of facilitating routing through a software-defined wide area network (SD-WAN) defined for an entity. A first edge forwarding node located at a first multi-machine site of the entity, the first multi-machine site at a first physical location and including a first set of machines, serves as an edge forwarding node for the first set of machines by forwarding packets between the first set of machines and other machines associated with the entity via other forwarding nodes in the SD-WAN. The first edge forwarding node receives configuration data specifying for the first edge forwarding node to serve as a hub forwarding node for forwarding a set of packets from a second set of machines associated with the entity and operating at a second multi-machine site at a second physical location to a third set of machines associated with the entity and operating at a third multi-machine site at a third physical location. The first edge forwarding node serves as a hub forwarding node to forward the set of packets from the second set of machines to the third set of machines.

Some embodiments of the invention provide a method of facilitating routing through a software-defined wide area network (SD-WAN) defined for an entity. A first edge forwarding node located at a first multi-machine site of the entity, the first multi-machine site at a first physical location and including a first set of machines, serves as an edge forwarding node for the first set of machines by forwarding packets between the first set of machines and other machines associated with the entity via other forwarding nodes in the SD-WAN. The first edge forwarding node receives configuration data specifying for the first edge forwarding node to serve as a hub forwarding node for forwarding a set of packets from a second set of machines associated with the entity and operating at a second multi-machine site at a second physical location to a third set of machines associated with the entity and operating at a third multi-machine site at a third physical location. The first edge forwarding node serves as a hub forwarding node to forward the set of packets from the second set of machines to the third set of machines.

A computer network optimization methodology is disclosed. In a computer-implemented method, components of a computing environment are automatically monitored, and have a feature selection analysis performed thereon. Provided the feature selection analysis determines that features of the components are in frequent communication and generating network latency. Provided the feature selection analysis determines that features of the components are not well defined, a similarity analysis of the features is performed. Results of the feature selection methodology are generated, and the components involved in the network traffic latency are reassigned to migrate the latency.