Abstract:
Techniques proactively deploy analytics to a computerized edge device. The techniques involve receiving data from the edge device. The data is conveyed through the edge device from a set of sensors disposed at a particular location. The techniques further involve performing analytics on the data to identify a set of edge device rules that defines a set of actions for the edge device to carry out under a set of predefined conditions potentially sensed by the set of sensors. The techniques further involve providing a command to the edge device. The command (i) includes the set of edge device rules and (ii) directs the edge device to, at a future time, start operating according to the set of edge device rules to protect against unsuccessful deployment of the command to the edge device due to subsequent delayed communication between the processing circuitry and the edge device.
Abstract:
The systems and methods discussed herein provide for a predictive monitoring technique to suppress data exchange between the client device or devices and the monitoring device or devices. Regression-based intelligent predictions systems executed both by the client device or devices and the monitoring device or devices perform identical prediction algorithms. If the predicted metric values and the actual measured metric values on the client device are very close, then the client device may skip transmitting the measured metric values to the monitoring device; similarly, if a measured metric value is not received by the monitoring device, then the monitoring device knows that the measured metric was similar to the predicted metric on the client device, and accordingly may utilize the predicted metric on the monitoring device. Because transmission of the measured metric values may be skipped, network traffic and interface and processor utilization is significantly decreased.
Abstract:
The systems and methods discussed herein provide for a predictive monitoring technique to suppress data exchange between the client device or devices and the monitoring device or devices. Regression-based intelligent predictions systems executed both by the client device or devices and the monitoring device or devices perform identical prediction algorithms. If the predicted metric values and the actual measured metric values on the client device are very close, then the client device may skip transmitting the measured metric values to the monitoring device; similarly, if a measured metric value is not received by the monitoring device, then the monitoring device knows that the measured metric was similar to the predicted metric on the client device, and accordingly may utilize the predicted metric on the monitoring device. Because transmission of the measured metric values may be skipped, network traffic and interface and processor utilization is significantly decreased.
Abstract:
Disclosed embodiments describe systems and methods for predicting health of a link. A device in communication with a link can identify profile information of a stream of network traffic traversing the link. The device can determine a first prediction of health of the link by applying one or more rules to the plurality of parameters of the profile information. The device can determine a second prediction of health of the link by applying a classifier to one or more timed sequences of the plurality of parameters of the profile information. The device can establishes a respective weight for each of the first prediction of health and the second prediction of heath. The device can select, using the respective weight, between the first prediction of health and the second prediction of health to provide a predictor of the health of the link.
Abstract:
The present invention is directed towards systems and methods for selecting a path or link from a plurality of links between intermediary devices, based on characteristics of links between the intermediary devices and end nodes of the communication flow. The link choice may be determined from latency, packet drop rates, jitter, congestion, or other characteristics of the links to the end nodes. Link selection may further be based on traffic priority or transport layer quality of service (QoS) requirements of the connection, load balancing requirements, or other such features.
Abstract:
A system for optimizing network traffic is described. The system includes a quality of service (QoS) engine configured to acquire information regarding a plurality of data packets comprising a plurality of data packet flows operating over a plurality of links. The QoS engine can be further configured to determine a flow priority to the plurality of data packets flows, and to determine TCP characteristics for the plurality of data packet flows. The system further includes a TCP controller configured to acquire the flow priority to the plurality of data packets from the QoS engine. The TCP controller can be configured to obtain queue information associated with the plurality of data packets, and adjust a receive window size based on the flow priority and the queue information.
Abstract:
A system for optimizing network traffic is described. The system includes a quality of service (QoS) engine configured to acquire information regarding a plurality of data packets comprising a plurality of data packet flows operating over a plurality of links. The QoS engine can be further configured to determine a flow priority to the plurality of data packets flows, and to determine TCP characteristics for the plurality of data packet flows. The system further includes a TCP controller configured to acquire the flow priority to the plurality of data packets from the QoS engine. The TCP controller can be configured to obtain queue information associated with the plurality of data packets, and adjust a receive window size based on the flow priority and the queue information.
Abstract:
The present invention is directed towards systems and methods for selecting a path or link from a plurality of links between intermediary devices, based on characteristics of links between the intermediary devices and end nodes of the communication flow. The link choice may be determined from latency, packet drop rates, jitter, congestion, or other characteristics of the links to the end nodes. Link selection may further be based on traffic priority or transport layer quality of service (QoS) requirements of the connection, load balancing requirements, or other such features.
Abstract:
An appliance o for evicting data based on traffic priority of data is described. The appliance has one or more processors and includes a compression history manager configured to acquire traffic priority information of data, the data being conveyed over a connection and to assign a compression history set based on the traffic priority information of the data. The compression history manager is also configured to, if cache space does not exist to store the data and another compression history set corresponds to lower traffic priority in a cache queue, evict data from the other compression history set corresponding to lower traffic priority.
Abstract:
A system for optimizing network traffic is described. The system includes a transport communication protocol (TCP) controller configured to acquire data regarding a flow of a plurality of data packets over a link and to determine TCP characteristics for the flow, a traffic prioritization module configured to assign a flow priority to the flow, and a traffic priority controller configured detect congestion on the link and determine a congestion window size for the flow based on the flow priority and the TCP characteristics.