A multi-member Bluetooth device for communicating data with a remote Bluetooth device is disclosed including: a main Bluetooth circuit and an auxiliary Bluetooth circuit. In the period during which the auxiliary Bluetooth circuit operates at a sniffing mode, the auxiliary Bluetooth circuit sniffs packets transmitted from the remote Bluetooth device while the main Bluetooth circuit receives packets issued from the remote Bluetooth device, and the auxiliary Bluetooth circuit switches from the sniffing mode to a relay mode if the throughput of packets sniffed by the auxiliary Bluetooth circuit is lower than a predetermined threshold. In the period during which the auxiliary Bluetooth circuit operates at the relay mode, the main Bluetooth circuit receives packets transmitted from the remote Bluetooth device and forwards the received packets to the auxiliary Bluetooth circuit, and the auxiliary Bluetooth circuit does not sniff packets issued from the remote Bluetooth device.

A multi-member Bluetooth device for communicating data with a remote Bluetooth device is disclosed including: a main Bluetooth circuit and an auxiliary Bluetooth circuit. In the period during which the auxiliary Bluetooth circuit operates at a sniffing mode, the auxiliary Bluetooth circuit sniffs packets transmitted from the remote Bluetooth device while the main Bluetooth circuit receives packets issued from the remote Bluetooth device, and the auxiliary Bluetooth circuit switches from the sniffing mode to a relay mode if the throughput of packets sniffed by the auxiliary Bluetooth circuit is lower than a predetermined threshold. In the period during which the auxiliary Bluetooth circuit operates at the relay mode, the main Bluetooth circuit receives packets transmitted from the remote Bluetooth device and forwards the received packets to the auxiliary Bluetooth circuit, and the auxiliary Bluetooth circuit does not sniff packets issued from the remote Bluetooth device.

Auto connectivity simulation from the client-side. Workstations/clients are intelligently selected, on a continuous basis, for auto connectivity simulation and probes are communicated to the selected workstations which activate a previously deployed agent that is configured to conduct connectivity simulations to the communication network and, at least, basic utility services provided within the communication network. The comprehensive results of connectivity simulations are analyzed and patterns of connectivity issues are identified. Subsequently, rules are applied to the patterns of connectivity issues to determine appropriate actions, such as reconfiguring the connectivity route, the servers used for connection and/or notifying personnel assigned to address the issues.

Auto connectivity simulation from the client-side. Workstations/clients are intelligently selected, on a continuous basis, for auto connectivity simulation and probes are communicated to the selected workstations which activate a previously deployed agent that is configured to conduct connectivity simulations to the communication network and, at least, basic utility services provided within the communication network. The comprehensive results of connectivity simulations are analyzed and patterns of connectivity issues are identified. Subsequently, rules are applied to the patterns of connectivity issues to determine appropriate actions, such as reconfiguring the connectivity route, the servers used for connection and/or notifying personnel assigned to address the issues.

This disclosure describes various methods, systems, and devices related to mirrored traffic forwarding in a hybrid network. An example method includes receiving, from a source forwarder in a source network, a mirrored data packet. A session of the mirrored data packet may be identified based on a header of the mirrored data packet. A destination forwarder in a destination network may be identified based on the session. The destination network may be different than the source network. The mirrored data packet may be forwarded to the destination forwarder.

A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying data center asset data to monitor; monitoring data center assets within a data center; selecting an asset data broker, the asset data broker performing an asset data aggregation operation, the asset data aggregation operation collecting and aggregating the data center asset data; and, providing aggregated data center asset data to a data center monitoring and management console.

This control system is provided with a controller, a controller which is a loopback communication device, a first communication route, and a second communication route. The controller generates and transmits control frames to slave devices. The controller performs loopback communication of the control frames. In the first communication route, multiple slave devices are connected between the controller and the controller using communication cables. In the second communication route, the first controller and the second controller are connected over a communication cable.

This control system is provided with a controller, a controller which is a loopback communication device, a first communication route, and a second communication route. The controller generates and transmits control frames to slave devices. The controller performs loopback communication of the control frames. In the first communication route, multiple slave devices are connected between the controller and the controller using communication cables. In the second communication route, the first controller and the second controller are connected over a communication cable.

In general, the disclosure describes techniques for measuring edge-based quality of experience (QoE) metrics. For instance, a network device may construct a topological representation of a network, including indications of nodes and links connecting the nodes within the network. For each of the links, the network device may select a node device of the two node devices connected by the respective link to measure one or more QoE metrics for the respective link, with the non-selected node device not measuring the QoE metrics. In response to selecting the selected node device, the network device may receive a set of one or more QoE metrics for the respective link for data flows flowing from the selected node device to the non-selected node device. The network device may store the QoE metrics and determine counter QoE metrics for data flows flowing from the non-selected node device to the selected node device.

In general, the disclosure describes techniques for measuring edge-based quality of experience (QoE) metrics. For instance, a network device may construct a topological representation of a network, including indications of nodes and links connecting the nodes within the network. For each of the links, the network device may select a node device of the two node devices connected by the respective link to measure one or more QoE metrics for the respective link, with the non-selected node device not measuring the QoE metrics. In response to selecting the selected node device, the network device may receive a set of one or more QoE metrics for the respective link for data flows flowing from the selected node device to the non-selected node device. The network device may store the QoE metrics and determine counter QoE metrics for data flows flowing from the non-selected node device to the selected node device.