A method for online monitoring of a physical environment using a variable data sampling rate is implemented by a computing device. The method includes sampling, at the computing device, at least one data set using at least one sampling rate. The method also includes processing the at least one data set with condition assessment rules. The method further includes determining whether the at least one data set indicates a change in state of the physical environment. The method additionally includes updating the at least one sampling rate.

Some embodiments of the invention provide a method for gathering data for logical network traffic analysis by sampling flows of packets forwarded through a logical network. Some embodiments are implemented by a set of network virtualization controllers that, on a shared physical infrastructure, can implement two or more sets of logical forwarding elements that define two or more logical networks. In some embodiments, the method (1) defines an identifier for a logical network probe, (2) associates this identifier with one or more logical observation points in the logical network, and (3) distributes logical probe configuration data, including sample-action flow entry data, to one or more managed forwarding elements that implement the logical processing pipeline at the logical observation points associated with the logical network probe identifier. In some embodiments, the sample-action flow entry data specify the packet flows that the forwarding elements should sample and the percentage of packets within these flows that the forwarding elements should sample.

A method is disclosed for performing a performance measurement on a packet flow transmitted along a path through a packet switched communication network. At least two measurement points implemented on the path calculate a sampling signature for each packet of the flow by applying a hash function to a mask of bits of the packet, and identify a sub-flow of measurement samples as those packets whose sampling signatures are equal to a certain value H*. The measurement points then provide measurement parameters for the measurement samples, which are used for providing performance measurement for the whole packet flow. Tailoring the length of the sampling signature allows the sampling rate to be statistically controlled so as to balance the risk of reception sequence errors between measurement samples and the computational effort on one hand, and the accuracy of the measurements provided on the other hand.

The disclosed techniques include at least one method. The method includes receiving, by a network device, incoming packets communicated over a computer network, and detecting flows to which the incoming packets belong. Each incoming packet belongs to a flow of the flows. The method further includes sampling each incoming packet that satisfies a flow condition having a flow interval of packets for the flow of the incoming packet, and sampling each incoming packet that satisfies a global condition having a global interval of packets irrespective of the flow of the incoming packet. The method further includes storing any sampled packets or information indicative of any sampled packets.

A system controls a transmission of data. A sensor datum measured by a sensor is received. Whether to send the received sensor datum to a multiplexer is determined based on a predefined real time download rate. When the determination indicates to send the received sensor datum to the multiplexer, the received sensor datum is sent to the multiplexer. When the determination does not indicate to send the received sensor datum to the multiplexer, the received sensor datum is written to a data file. The written sensor datum is sent from the data file to the multiplexer when there is an indicator of excess available bandwidth.

Some embodiments provide a method of identifying packet latency in a software defined datacenter (SDDC) that includes a network and multiple host computers executing multiple machines. At a first host computer, the method identifies and stores (i) multiple time values associated with several packet processing operations performed on a particular packet sent by a first machine executing on the first host computer, and (ii) a time value associated with packet transmission through the SDDC network from the first host computer to a second host computer that is a destination of the particular packet. The method provides the stored time values to a set of one or more controllers to process to identify multiple latencies experienced by multiple packets processed in the SDDC.

Embodiments of the disclosure pertain to activating in-band OAM based on a triggering event. Aspects of the embodiments are directed to receiving a first notification indicating a problem in a network; triggering a data-collection feature on one or more nodes in the network for subsequent packets that traverse the one or more nodes; evaluating a subsequent packet that includes data augmented by the data collection feature; and determining the problem in the network based on the data augmented to the subsequent packet.

A system for detecting the topology and phase information of an electrical power distribution system is provided. For example, the system includes a group of meters connected to an electrical power distribution system and can communicate with each other through local network connections such as a mesh network. Each of the meters is configured to generate and transmit voltage data to a correlator of the group of meters. The correlator calculates the correlations between each pair of meters in the group based on the voltage data received and further transmits the calculated correlations to a mapper through the mesh network. The mapper determines the topological or phase relationship between at least the group of meters based on the received correlations.

The present disclosure relates to system(s) and method(s) for predicting a Key Performance Indicator (KPI) in a telecommunication network is illustrated. The system is configured to monitor a set of counters and a Key Performance Indicator corresponding to a telecommunication network. The set of counters and the Key Performance Indicator (KPI) are monitored for a predefined time interval to gather sample data. The system is configured to analyze the sample data using a data analysis technique in order to identify a subset of counters, from the set of counters, influencing the KPI and a correlation coefficient associated with each counter from the subset of counters, wherein the correlation coefficient associated with each counter is identified after normalizing the subset of counters. The system is configured to apply regression on the subset of counters and the KPI in order to build a correlation equation between the subset of counters and the KPI.

A network visibility appliance automatically and dynamically determines a data traffic sampling policy that it should apply, i.e., a policy for determining which flows the network appliance should forward to one or more tools. The technique can be used to adjust for changes in network traffic to avoid exceeding performance constraints (e.g., maximum throughput) of network analytic tools, while maintaining high efficiency of usage of the tools. In the technique, a policy engine monitors network traffic characteristics in a subscriber throughput table and dynamically determines a sampling policy to apply, so as to decrease and/or increase traffic throughput to a given tool, so that the tool is efficiently used.