LEARNING-BASED SERVICE MIGRATION IN MOBILE EDGE COMPUTING

    公开(公告)号:US20200320397A1

    公开(公告)日:2020-10-08

    申请号:US16375315

    申请日:2019-04-04

    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.

    LEARNING-BASED SERVICE MIGRATION IN MOBILE EDGE COMPUTING

    公开(公告)号:US20210406696A1

    公开(公告)日:2021-12-30

    申请号:US17474191

    申请日:2021-09-14

    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.

    MU-MIMO GROUPING SYSTEM
    3.
    发明申请

    公开(公告)号:US20180234141A1

    公开(公告)日:2018-08-16

    申请号:US15431539

    申请日:2017-02-13

    CPC classification number: H04B7/0452 H04L41/0893 H04L43/0894

    Abstract: Embodiments herein describe a network device (e.g., an access point) that dynamically arranges multi-user (MU) multiple input multiple output (MIMO) compatible client devices into MU-MIMO groups. That is, the network device uses network metrics and historical data to change the assignment of client devices in the MU-MIMO groups which may improve MU-MIMO efficiency by reducing the amount of power that leaks between the clients devices in the group. In one embodiment, the AP identifies a MU-MIMO group based on a performance evaluation such as evaluating network metric or determining if the group is underutilized. The AP can replace the identified MU-MIMO group with a substitute MU-MIMO group where the substitute MU-MIMO group is selected based on historical data corresponding to the client devices assigned to the substitute MU-MIMO group.

    MULTI-USER GROUPING
    5.
    发明申请
    MULTI-USER GROUPING 审中-公开

    公开(公告)号:US20190140791A1

    公开(公告)日:2019-05-09

    申请号:US15803785

    申请日:2017-11-05

    Abstract: In one embodiment, a system includes a processor to determine a number P of how many multi-user groups are to be formed to promote airtime fairness for N client devices in which each one client device of the N client devices will be equally represented in the to-be-formed multi-user groups and in which each of the to-be-formed groups is to be actively considered by a scheduler for transmission purposes, the N client devices being associated with N wireless connections with an access point having multi-user simultaneous communication multiple-input multiple-output technology, define P multi-user groups with each one multi-user group of the P multi-user groups having a capacity for M client devices from the N client devices, N being greater than M, and allocate the N client devices to the P multi-user groups with each one client devices of the N client devices being equally represented in the P multi-user groups.

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