Cisco Technology, Inc.

Prosimo Inc

Santosh Ghanshyam Pandey

Jean-Philippe Vasseur

Brian Donald Hart

Rong Peng

Abhishek Mukherji

Matthew Aaron Silverman

Paul Jeffrey Stager

Jerome Henry

Vinay Kumar Kolar

Pooya Monajemi

Huy Phuong Tran

Xu Zhang

Vishal Satyendra Desai

David Stuart Kloper

Vikram Kumaran

Vinay S Raghuram

Grégory Mermoud

Andrew Frederick Myles

Abhishek Bhattacharyya

Sidhesh Divekar

Dan Lyons

Jiang Zhu

David Sheldon Stephenson

Xiaoqing Zhu

Hugo Latapie

Enzo Fenoglio

Hui Liu

Tak Ming Francis Pang

Rob Liston

Jagdish Girimaji

Mehdi Nikkhah

Oscar Bejarano Chavez

Sajjit Thampy

Balaji Gurumurthy

Prasad Walawalkar

Senthil Nathan Chockalingam

Ilya Khasin

Shaunak Joshi

Robert Edgar Barton

Sukrit Dasgupta

Allen Huotari

Allan Thomson

Wai-Tian Tan

John Matthew Swartz

Andre Surcouf

Stephen Michael Orr

Rohit Kumar Suri

Zhigang Gao

Raghuram Rangarajan

Preethi Natarajan

Abhishek Kumar

Sujai Hajela

Shaun Kirby

Jagadish Chundury

Justin James Muller

Kayshav Dattatri

Greg Corsetto

Jacob Earl Fussell

Liu Huang

Matt Silverman

Victor Tsekay To

Oscar Berjarano Chavez

Edmund Cameron Duhaime

Federico Lovison

Matthew A Sliverman

Gerard Ian McGarry

Wai-tan Tan

Anshul Tyagi

Donald R Peoples

Deepak Badri

Techniques to determine location-related data for a plurality of access points located in an area in communication with a network by determining that a plurality of access points in a network are associated with a same geographical area including identifying, from among the plurality of access points, a first access point associated with the geographical area, determining first location-related data for the first access point, determining second location-related data for a second access point of the plurality of access points, the second access point being interior to the first access point within the network based at least in part on the second access point having at least a threshold number of the neighbor access points, and exchanging ranging data indicative of a first relative distance between the first access point and the second access point, the ranging data based at least in part on ranging message exchange measurements.

Systems and methods for determining locations of access points

Techniques to determine location-related data for a plurality of access points located in an area in communication with a network by determining that a plurality of access points in a network are associated with a same geographical area including identifying, from among the plurality of access points, a first access point associated with the geographical area, determining first location-related data for the first access point, determining second location-related data for a second access point, the second access point being interior to the first access point within the network based at least in part on a determination that the second access point has at least a threshold number of the neighbor access points, and exchanging ranging data indicative of a first relative distance between the first access point and the second access point, the ranging data based at least in part on ranging message exchange measurements.

Edge clusters execute in a plurality of regional clouds of a cloud computing platforms, which may include cloud POPs. Edge clusters may be programmed to control access to applications executing in the cloud computing platform. Edge clusters and an intelligent routing module route traffic to applications executing in the cloud computing platform. Cost and latency may be managed by the intelligent routing module by routing requests over the Internet or a cloud backbone network and using or bypassing cloud POPs. The placement of edge clusters may be selected according to measured or estimated latency. Latency may be estimated using speed test servers and the locations of speed test servers may be verified.

Estimation of latency across regional clouds

Systems, methods, and computer-readable media may determine location-related data for a plurality of access points located in an area in communication with a network by determining that a plurality of access points in a network are associated with a same geographical area including identifying, from among the plurality of access points, a first access point associated with the geographical area, determining first location-related data for the first access point, determining second location-related data for a second access point of the plurality of access points, the second access point being interior to the first access point within the network based at least in part on a determination that the second access point has at least a threshold number of the neighbor access points, and exchanging ranging data indicative of a first relative distance between the first access point and the second access point, the ranging data based at least in part on ranging message exchange measurements.

Access Point (AP) placement using Fine Time Measurement (FTM) may be provided. First, a plurality of Time-of-Flight (ToF) values between a first service end point and a second service end point may be determined. Each one of the plurality of ToF values may be derived from packets transmitted via different beamforming vector patterns at the first service end point and the second service end point. Then a minimum ToF value of the plurality of ToF values may be determined. Next, a distance between the first service end point and the second service end point may be determined based on the minimum ToF value.

Access Point (AP) placement using Fine Time Measurement (FTM)

In one embodiment, a network assurance service that monitors a network maps time series of values of key performance indicator (KPIs) measured from the network to lists of unique values from the time series. The service sets a target alarm rate for anomaly detection alarms raised by the network assurance service. The service uses an optimization function to identify a set of thresholds for the KPIs. The optimization function is based on: a comparison between the target alarm rate and a fraction of network issues flagged by the service as outliers, KPI thresholds selected based on the lists of unique values from the time series, and a number of thresholds that the KPIs must cross for the service to raise an alarm. The service raises an anomaly detection alarm for the monitored network based on the identified set of thresholds for the KPIs.

Threshold selection for KPI candidacy in root cause analysis of network issues

In one embodiment, a network assurance service that monitors a wireless network identifies a set of wireless network anomalies detected in the wireless network that are associated with a set of one or more network measurements. The network assurance service classifies the set of wireless anomalies as radio-related or backend-related. The network assurance service, when the set of wireless anomalies are classified as radio-related, determines that the wireless anomalies are recurring for a particular wireless access point in the network. The network assurance service initiates a change to the wireless network in part to move clients in the wireless network from the particular wireless access point to another wireless access point in the network.

Machine learning-based approach to network planning using observed patterns

In one embodiment, a method includes receiving a plurality of radio frequency chains at a wireless device in a block based modulation environment, recording subcarrier phases and differences between the subcarrier phases, and using the subcarrier phase differences to construct a feature vector for use in angle of arrival calculated positioning of a mobile device.

Angle of arrival location sensing with antenna array

Estimating speedtest server accuracy

A system may be configured to identify from among a plurality of access points in an area in communication with a network, a first access point associated with the area. In addition the system may also be configured to determine first location-related data for the first access point. Determining second location-related data for a second access point of the plurality of access points, the second access point being interior to the first access point within the network includes exchanging ranging data indicative of a first relative distance between the first access point and the second access point, the ranging data based at least in part on ranging message exchange measurements, and communicating the first location-related data from the first access point to the second access point.

Offloading of location computation from a location server to an access point through the use of projections on base phase vectors may be provided. First, an Access Point (AP) may receive a set of two or more base phase vectors from a location server. Next, the AP may measure a measured phase vector for a first signal from a user device. Then, the AP can determine projection values based on a comparison of the measured phase vector to each base phase vector. From these comparisons, the AP can determine a subset of base phase vectors with the highest projection values. The AP can then send the projection values and the subset of base phase vectors to the location server, wherein the location server determines the device location from these projection values and subset of base phase vectors.

Offloading location computation from cloud to access point (AP) with projection on base phase vectors

Access point (AP) placement using fine time measurement (FTM)

Client analytics-driven dynamic channel assignment may be provided. At a client, Radio Frequency (RF) channels may be scanned to detect access points of a network. A subset of the access points belonging to a same Extended Set Service (ESS) of the network may be determined based on data collected from the access points during the scan. For each access point in the subset, a Channel Quality Index (CQI) may be measured for an RF channel assigned to the access point, and a non-preferred channel report may be generated based on the CQI. The non-preferred channel report may be transmitted from the client to a network management system for use in dynamic channel assignment.

Dynamic channel assignment driven by client analytics

In one embodiment, a network assurance service that monitors a network detects, using a machine learning-based anomaly detector, network anomalies associated with source nodes in the monitored network. The network assurance service identifies, for each of the detected anomalies, a set of network paths between the source nodes associated with the anomaly and one or more potential destinations of traffic for that source node. The network assurance service correlates networking devices along the network paths in the identified sets of network paths with the detected network anomalies. The network assurance service adjusts the machine learning-based anomaly detector to use a performance measurement for a particular one of the networking devices as an input feature, based on the correlation between the particular networking device and the detected network anomalies.

Dynamic inspection of networking dependencies to enhance anomaly detection models in a network assurance service

Growing community of inventors

Fremont, CA, United States of America

Santosh Ghanshyam Pandey