-
公开(公告)号:US10925001B2
公开(公告)日:2021-02-16
申请号:US16407447
申请日:2019-05-09
Applicant: Cisco Technology, Inc.
Inventor: Gautam Dilip Bhanage , Pooya Monajemi , Khashayar Mirfakhraei , Ardalan Alizadeh , Xu Zhang
Abstract: In one embodiment, a device in a wireless network receives a target wake time (TWT) request from a wireless client. The device computes TWT parameters based on the received request. The device predicts, using the computed TWT parameters as input to a machine learning model, whether the computed TWT parameters will be accepted by the wireless client. The device provides the computed TWT parameters to the wireless client, based on a prediction by the machine learning model that the client will accept the computed TWT parameters.
-
公开(公告)号:US20200320397A1
公开(公告)日:2020-10-08
申请号:US16375315
申请日:2019-04-04
Applicant: Cisco Technology, Inc.
Inventor: Dantong LIU , Qing ZHAO , Khashayar MIRFAKHRAEI , Gautam Dilip BHANAGE , Xu Zhang , Ardalan Alizadeh
Abstract: Learning-based service migration in mobile edge computing may be provided. First, a service migration policy may be created for a network that includes a plurality of edge clouds configured to provide a service to users. Next, a movement of a user receiving the service from a source edge cloud may be detected. The source edge cloud may be associated with a first area and the detected movement may be from the first area to a second area. Then, the service migration policy may be applied to determine whether to migrate the service for the user from the source edge cloud. In response to determining to migrate the service, a target edge cloud may be identified and the service for the user may be migrated from the source edge cloud to the target edge cloud. The service migration policy may then be updated based on a success of the migration.
-
公开(公告)号:US20200296611A1
公开(公告)日:2020-09-17
申请号:US16299481
申请日:2019-03-12
Applicant: Cisco Technology, Inc.
Inventor: Khashayar Mirfakhraei , Xu Zhang , Ardalan Alizadeh , Amir Hosein Kamalizad
Abstract: In one embodiment, an apparatus comprises a compressive sensing schedule generator configured to generate a plurality of compressive sensing schedules, wherein each of the plurality of compressive sensing schedules is for each of a plurality of frequency bands of a network, wherein the network comprises a plurality of access points and a plurality of clients, and a sensing matrix combiner configured to combine the plurality of compressive sensing schedules into a resulting schedule that comprises a spatial distribution and a scheduled time slot for each of the plurality of access points.
-
-