A 10 Networks, Incorporated

F5 Networks, Inc.

Gennady Dosovitsky

Rajkumar Ramniranjan Jalan

Ron Talmor

Kishore Inampudi

Dmitry Rovniaguin

Paul Imre Szabo

Saxon Carl Amdahl

Gurudeep Kamat

Swaminathan Sankar

David Alan Hansen

Sumandra Majee

Dan Karpati

Jeroen De Borst

David A Hansen

Amir Harush

Assaf Jacob Mendelson

Dan Eliezer Karpati

Provided are methods and systems for adjusting subscriber policies. A method for adjusting of subscriber policies may include applying traffic enforcement rules to a data traffic associated with a subscriber. The method can further include determining network conditions associated with the data traffic. The method can include modifying, based on the determination of the network conditions, attributes according to attribute adjustment rules to obtain modified attributes. The method can further include modifying the traffic enforcement rules based on the modified attributes to obtain modified traffic enforcement rules.

Automated adjustment of subscriber policies

Methods, non-transitory computer readable media, network traffic management apparatuses, and network traffic management systems that obtain an assigned Internet Protocol (IP) address from a DHCP server in response to an address request received from a client. One of a plurality of processing cores, on which a traffic management process is executing, is identified. The assigned IP address is modified based on the identified processing core. The modified IP address is sent to the client in response to the received address request. With this technology, connections associated with a same subscriber can advantageously be disaggregated to the same traffic management process.

Methods for disaggregating subscribers via DHCP address translation and devices thereof

Provided are methods and systems for eliminating a redirection of data traffic in a cluster. An example method may include receiving, by one or more nodes of the cluster, a data packet associated with a service session. The method may include determining, by the node, that the data packet is directed to a further node in the cluster. The method may further include, in response to the determination, acquiring, by the node, a session context associated with the service session. Acquiring the session context may include sending, by the node, a request for the session context to the further node and receiving the session context from the further node. The method may further include processing, by the one or more nodes, the data packet based on the session context.

Eliminating data traffic redirection in scalable clusters

Decreasing a volume of data transfer over a network may commence with collecting a plurality of datasets having subscriber data. The method may continue with classifying data fields of each dataset of the plurality of datasets into low frequency change data and high frequency change data based on predetermined criteria. The method may further include combining a plurality of consecutive datasets of the plurality of datasets into a combination dataset. The combination dataset may include the low frequency change data and aggregated high frequency change data from the plurality of consecutive datasets. The method may continue with providing the combination dataset to a data processing node.

Reduction of volume of reporting data using multiple datasets

Decreasing data transfer over a network may commence with collecting subscriber data. The method may continue with classifying the subscriber data into low frequency change data and high frequency change data based on predetermined criteria. The method may include storing the low frequency change data to a data storage. The method may continue with generating reporting data. The reporting data may include the high frequency change data and at least one data index pointer to the low frequency change data in the data storage. The method may further include providing the reporting data to a data processing node. The low frequency change data may include subscriber identifying data. The data reporting node may be further configured to obfuscate the subscriber identifying data. The at least one data index pointer may include a secure data identifier associated with the obfuscated subscriber identifying data.

Reduction of volume of reporting data using content deduplication

Embodiments are directed towards using policy rules that may be extended by scripting operative on a traffic management device. Each policy rule may have a condition and a corresponding action. If the condition is a script, a script engine separate from the policy engine may be employed to execute the script to determine if the condition is met. Otherwise, the policy engine may determine if the condition is met based on declarative expressions that comprise the condition. If the condition is met the action corresponding to the policy rule may be executed. Scripts may be used to compute the values of operands that may be used in one or more of the expression that comprise a condition for a policy rule. Also, the action corresponding to a policy rule may be implemented using a script that is executed by a script engine.

Extending policy rulesets with scripting

Provided are methods and systems for adjusting of subscriber policies. A method for adjusting of subscriber policies may include applying traffic enforcement rules to a data traffic associated with a subscriber. The method can further include determining network conditions associated with the data traffic. The method can include modifying, based on the determination of the network conditions, attributes according to attribute adjustment rules to obtain modified attributes. The method can further include modifying the traffic enforcement rules based on the modified attributes to obtain modified traffic enforcement rules.

Embodiments are directed towards managing communication over a network assist application classification using predicted subscriber behavior. Subscriber information associated with a network flow may be determined. Prediction information that includes application identifiers may be generated based on the subscriber information. A classification engine may determine the applications associated with the network flow based on the prediction information and the network flow using a plurality of application classifiers that correspond to the applications. If an application identifier included in the prediction information is correspondent to an application classifier, the application may be determined based on the correspondent application classifier; otherwise the application is determined based on the remainder of the application classifiers. A policy for managing the network flow may be determined based on the determined application. Then the network traffic associated with the network flow may be communicated based on the at least one determined policy.

Assisting application classification using predicted subscriber behavior

Embodiments are directed towards managing communication over a network with a packet traffic management device that performs delayed proxy action. The PTMD includes a buffer for buffering network traffic. Also, the PTMD includes proxy data paths and standard data paths. Network policies associated with the network flows may be determined using the buffered data. If a determined network policy includes proxy policy rules it is a proxy network policy. Then the network flows are associated with a proxy data path. If the buffer is exhausted, the network flow is associated with a standard data path before a policy is determined. Otherwise, if the network policy includes only standard policy rules, the network flows are moved to a standard data path. After the network flow is associated with a data path, the network traffic may be communicated until it is closed or otherwise terminated.

Delayed proxy action

Provided are methods and systems for processing a secure data flow. An example method for processing a secure data flow includes receiving a data packet, determining network conditions associated with the data traffic, and determining that the data packet is associated with the secure data flow. Upon determination that the data packet is associated with the secure data flow, the data packet is analyzed. Thereafter, the method proceeds to classify the secure data flow based on the analysis. Subscriber data associated with the data packet may be obtained. The method can then process the secure data flow based on the subscriber data and the classification of the secure data flow.

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Sunnyvale, CA, United States of America

Gennady Dosovitsky