Hewlett Packard Enterprise Development LP

Hewlett-packard Development Company, L.P.

Rangaprasad Sampath

Madhusoodhana Chari Sesha

Venkatavaradhan Devarajan

Parikshit Misra

Ankita Agrawal

Sriharsha Tallapakam

Abhay Bhaskar

Shree Phani Sundara B N

Ravindra Guntur

Anand Eswaran

Anoop Kumaran Nair

Ankit Kumar Sinha

Krishna Mohan Elluru

Praveen Kumar Arora

Ramlakhan Patel

Ramasamy Apathotharanan

Vamsi Krishna Devaki

Radhakrishnan Sivaraman

Esteban Rodriguez Betancourt

Pramod Kumar A S

Radhika Hegde Manjeshwar

Sudhir Kumar ChimakurthyOm

A device may determine sample points associated with network routes within a network during a time interval, wherein each sample point that is associated with a respective network route comprises an amount of uptime for the respective network route during the time interval and a total frequency of state changes for the respective network route during the time interval. The device may generate, using an unsupervised machine learning mechanism, clusters of the sample points and may label the network routes with route stability labels based at least in part on the clusters. The device may generate, using a supervised machine learning mechanism, a route stability classifier based at least in part on the route stability labels for the network routes, and may determine, using the route stability classifier, a route stability of a new network route within the network.

Network route stability characterization

An example method can include tracking, by a network device, a plurality of attributes associated with a plurality of unique client device identifiers stored in a tracking table; deriving, by the network device, a training data set based on the plurality of attributes; and generating, by the network device, a plurality of clusters by inputting the derived training data set to an unsupervised machine learning mechanism. The example method can include receiving, by the network device, a labeling of the plurality of unique client device identifiers in the tracking table based at least on the plurality of clusters; generating, by the network device, a plurality of classifiers by inputting the labelled tracking table to a supervised machine learning mechanism; and classifying, by the network device, a new unique client device identifier in the tracking table based at least on the plurality of classifiers.

Device identifier classification

An example method can include tracking, by a network device, a plurality of database operations performed and a plurality of expected database operations for an event that executes for a time period, generating, by the network device, a plurality of clusters based on a ratio of the database operations performed compared to the plurality of expected database operations and the time period for the event, classifying, by the network device, the clusters based on performance, and evaluating, by the network device, a system performance metric based on a classification of real time data into the clusters.

Database operation classification

Examples provided herein describe a method for providing security for Internet of Things (IoT) devices. For example, a data packet from an IoT device may be received at an edge device. A signature associated with the IoT device may be accessed at the edge device, where the signature includes network layer information about the IoT device. A set of rules may be applied by the edge device to validate the IoT device based on the accessed signature. Responsive to the IoT device being validated based on the accessed signature, received data packet, and the applied set of rules, the edge device may process the data packet from the IoT device.

Providing security for internet of things (IoT) devices

One embodiment of the present invention provides a switch. The switch includes a storage device, a processing module, and a database module. The storage device can maintain a database storing configuration information for the switch. During operation, the processing module produces a piece of data associated with operations of the switch based on the configuration information. The database module then stores the piece of data in a database table of the database without caching the piece of data in a memory of the switch after the piece of data is stored in the database. In this way, the database module can reduce the memory occupancy of the processing module in comparison with the storage occupancy of a schema corresponding to the database table. Subsequently, the processing module can program a hardware module of the switch with the piece of data prior to receiving an acknowledgment from the database module.

Method and system for database enhancement in a switch

A method, system, and computer-readable storage device for detecting conflicts in a hybrid network device is described herein. A hybrid network device may receive a local controller command from a network management device (e.g., a laptop, operated by a network administrator, executing a command line interface). The hybrid network device may convert the local controller command to a software defined command format. The hybrid network device may detect a lack of conflict between the converted local controller command and active flows represented in an active flow repository. Based on the detected lack of conflict, the hybrid network device may update a traffic forwarding table of the hybrid network device in accordance to the local controller command.

Conflict detection in a hybrid network device

A hybrid software defined networking (SDN) switch has a forwarding table including local flow entries and SDN flow entries. In one example, the hybrid SDN switch may send both local flow entries and SDN flow entries to a SDN controller.

Forwarding table of hybrid software defined networking switch

In one example, a software-defined networking (SDN) controller can access flow capability information for flow paths along network data path elements in the control plane of the SDN controller. The SDN controller can determine network compatibility for an SDN controller application based on whether the accessed flow capability information fails to meet a flow requirement for the application. The SDN controller can further notify the application when it is determined that the flow requirements for the application are not met by a flow path. Related methods and machine-readable storage mediums are also described.

Network compatibility determination based on flow requirements of an application and stored flow capabilities of a software-defined network

A match field and an action for a flow rule may be received from a software defined networking application. A mapping of table identifications to attributes may be analyzed to obtain a table identification. The table identification may be for a pipeline table of a network device. The pipeline table may be able to implement the match field and the action.

Pipeline table identification

Implementing gateway redundancy in a network includes sending a message to a first device of multiple devices of a network through a controller where the first device is a master gateway and a second device of the multiple devices is a backup gateway, and making a decision as to whether the first device remains as the master gateway.

Implementing gateway redundancy in a network

Provided is a method of troubleshooting an OpenFlow network. A test packet is sent to a test node on the OpenFlow network. A response from the test node is validated against an expected response. If the response is consistent with the expected response, a modified test packet is sent to a further test node on the OpenFlow network. If the response is inconsistent with the expected response, a notification is provided to a user.

Troubleshooting openflow networks

A method and system for operating a virtual router system. A system health index for each of a plurality of physical routers in a virtual router system is determined, and virtual router operation for the physical routers is suspended in response to the system health index.

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Bengaluru, India

Rangaprasad Sampath