公开(公告)号：US20190107396A1

公开(公告)日：2019-04-11

申请号：US15726537

申请日：2017-10-06

Applicant: Cisco Technology, Inc.

Inventor： Wai-tian Tan ,  Rob Liston ,  Xiaoqing Zhu ,  Mehdi Nikkhah ,  Santosh G. Pandey

IPC: G01C21/00 ,  H04B17/318 ,  G01C21/20 ,  G01C21/16

Abstract: A methodology includes determining coarse location coordinates for a mobile device, anchoring the coarse location coordinates to a map, receiving inertial measurement unit data supplied by the mobile device, wherein the inertial measurement unit data is indicative of relative location coordinates of the mobile device, generating an unanchored path of the mobile device based on the relative location coordinates, and anchoring the unanchored path of the mobile device to the map in a position that optimizes a match between the coarse location coordinates and the relative location coordinates of the mobile device.

公开(公告)号：US10234291B1

公开(公告)日：2019-03-19

申请号：US15726537

申请日：2017-10-06

Applicant: Cisco Technology, Inc.

Inventor： Wai-tian Tan ,  Rob Liston ,  Xiaoqing Zhu ,  Mehdi Nikkhah ,  Santosh G. Pandey

IPC: H04B17/00 ,  G01S5/06 ,  G01C21/00 ,  H04W64/00 ,  G01C21/16 ,  G01C21/20 ,  H04B17/318

Abstract: A methodology includes determining coarse location coordinates for a mobile device, anchoring the coarse location coordinates to a map, receiving inertial measurement unit data supplied by the mobile device, wherein the inertial measurement unit data is indicative of relative location coordinates of the mobile device, generating an unanchored path of the mobile device based on the relative location coordinates, and anchoring the unanchored path of the mobile device to the map in a position that optimizes a match between the coarse location coordinates and the relative location coordinates of the mobile device.

公开(公告)号：US20180137412A1

公开(公告)日：2018-05-17

申请号：US15352938

申请日：2016-11-16

Applicant: Cisco Technology, Inc.

Inventor： Mehdi Nikkhah ,  Preethi Natarajan

IPC: G06N3/08 ,  H04L12/24

CPC classification number: H04L41/147 ,  G06N3/0445 ,  G06N3/084 ,  H04L41/0896 ,  H04L41/16 ,  H04L43/067 ,  H04L43/0894

Abstract: A server uses an LSTM neural network to predict a bandwidth value for a computer network element using past traffic data. The server receives a time series of bandwidth utilization of the computer network element. The time series includes bandwidth values associated with a respective time values. The LSTM neural network is trained with a training set selected from at least a portion of the time series. The server generates a predicted bandwidth value associated with a future time value based on the LSTM neural network. The provisioned bandwidth for the computer network element is adjusted based on the predicted bandwidth value.