Cisco Technology, Inc.

Kedar Krishnanand Gaonkar

Rajesh S Pazhyannur

Mark Grayson

Santosh Ramrao Patil

Gangadharan Byju Pularikkal

Waseem A Siddiqi

Aruna Nukala

Anand K Oswal

Sudhir Kumar Jain

Shree N Murthy

Arun G Khanna

Jerome Henry

Robert Edgar Barton

Abhishek Dhammawat

Sujit Biswas

Manjula Shivanna

Ather Sayeed Kanak

Aleksandar Miodrag Ivanovic

Techniques are presented herein for provisioning network devices based on device type. In one example, a packet core gateway of a cellular core network identifies a device type of a network device and obtains an indication to provision the network device. In response to obtaining the indication to provision the network device, the packet core gateway provisions the network device with one or more network resources based on the device type of the network device.

Network device provisioning based on device type

Certain embodiments disclose systems and methods for creating a user private network (UPN) based on 11ay technology. Methods of the present disclosure include creating a personal basic service set (PBSS) having a service device and one or more 11ay devices, the service device configured to wirelessly communicate with the one or more 11ay devices in the PBSS, creating a UPN having an access point located in communicative proximity with the service device, and associating at least one 11ay device of the one or more 11ay devices with the UPN, wherein the at least one 11ay device is configured to establish a wireless connection with the one or more 11ay devices using the service device when within a coverage area of the PBSS, and to establish a wireless connection with the one or more 11ay devices using the access point when outside the coverage area of the PBSS.

Creating a user private network based on 802.11ay Wi-Fi technology

A method of controlling performance of a wireless device is performed by a node that is in electronic communication with a cellular network. The node includes a processor, a non-transitory memory, and a network interface. The method includes receiving a performance value characterizing a performance of a communication channel between a wireless device and a wireless access point. In some implementations, the wireless device and the cellular network are associated with different radio access technologies (RATs). The method includes determining whether the performance value breaches a performance criterion for the wireless device. The method includes adjusting a first amount of data transmitted to the wireless device from a base station of the cellular network and a second amount of data transmitted to the wireless device from the wireless access point. In some implementations, the combined first and second amounts of data satisfy the performance criterion for the wireless device.

Controlling performance of a wireless device in a heterogeneous network

Systems, methods and computer-readable storage media are provided for detecting and simulating issues in a network. The methodology includes identifying: event sequences within network traffic data; filtering out a subset of the event sequences based on characteristics of the subset of the event sequences; generating definition groups by performing clustering on the subset of the event sequences, the definition groups comprising event sequence characteristics associated with one or more network issues; first simulating the subset of the event sequences; generating, based on results of the first simulating, a first issue identification; second simulating a most recent one of the identified event sequences; generating, based on results of the second simulating and the generated definition groups, a second issue identification; and validating the first issue identification with the second issue identification.

System and methods to validate issue detection and classification in a network assurance system

Systems, methods and computer-readable storage media are provided for detecting and simulating issues in a network.

A request is received from a client device to connect to a wireless network associated with a cloud computing device. A first notification is received to indicate that a first client transaction has started. Using a first timer, a first timestamp associated with a start time of the first client transaction is identified. A first data frame having the first client transaction and the first timestamp is generated. A second notification indicating that the first client transaction has completed is received. Using the first timer, a second timestamp associated with an end time of the first client transaction is identified. Using the second timestamp, the first data frame is updated using the second timestamp. The first data frame is sent to the cloud computing device.

Transaction-based event tracking mechanism

In one embodiment, a device in a network determines behavioral profiles of a plurality of nodes in the network. The behavioral profile for a particular node indicates whether the node is an occasional transmitter or a periodic transmitter. The device identifies similarly behaving nodes based on their behavioral profiles. The device assigns groups of the nodes to uplink transmission windows based on their behavioral profiles. The similarly behaving nodes that are periodic transmitters are assigned to the same uplink transmission windows and similarly behaving nodes that are occasional transmitters are assigned to different uplink transmission windows. The device controls the plurality of nodes to use their assigned uplink transmission windows via target wake time values sent to the plurality of nodes.

Target wake time and grouping scheme for IoT transmitters

Predicting data throughput with a user device comprises a wireless system supported by wireless access points receiving signals from the user device. A wireless prediction system receives data from the wireless system, where the data comprises characteristics of the wireless access point, characteristics of communications with user computing devices, and data throughput statistics. The prediction system categorizes the received data based on one or more of a set of characteristics and determines a maximum data throughput capacity for each of the one or more wireless access points for each of the one or more set of characteristics. The system receives a request for a prediction of data throughput capacity for a particular wireless access point and, based on the characteristics of the particular wireless access point, determines an estimated data throughput capacity based on data throughputs of wireless access points having similar characteristics.

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San Jose, CA, United States of America

Kedar Krishnanand Gaonkar