WEB CONFERENCE DATA VISUALIZATION
    23.
    发明公开

    公开(公告)号:US20240250838A1

    公开(公告)日:2024-07-25

    申请号:US18159190

    申请日:2023-01-25

    CPC classification number: H04L12/1822 G06T11/206

    Abstract: Aspects of the present disclosure relate to data visualization in web conferences. Type-related information of a web conference can be acquired. A conference type of the web conference can be identified based on the acquired type-related information of the web conference and type templates stored in a type repository. A visualization format from a plurality of visualization formats stored in a format repository can be determined based on the identified conference type. Key information required by the determined visualization format can be extracted from raw data of the web conference. Visual data within the determined visual format can be created by populating the extracted key information into the determined visualization format.

    DYNAMIC DATA COLLECTION
    24.
    发明公开

    公开(公告)号:US20240241885A1

    公开(公告)日:2024-07-18

    申请号:US18155242

    申请日:2023-01-17

    CPC classification number: G06F16/2477 G06F16/24564

    Abstract: Disclosed embodiments provide techniques for dynamic data collection. The dynamic data collection includes determining a data generation temporal pattern. Based on the data generation temporal pattern, a data collection strategy is created. The data collection strategy can be based on one or more data collection goals. The data collection strategy can contain specific details on how data is to be collected. A data infrastructure evaluation is performed, which provides pricing models for resources such as electricity and/or network bandwidth. A data collection policy is created based on the data collection strategy and the data infrastructure evaluation. The data collection policy can contain specific details on when data is to be collected and what strategy to use for the collection. A data transfer schedule is created based on the data collection policy. The data transfer schedule determines when to collect data from one or more data source devices.

    IMAGE OPTIMIZATION FOR PIPELINE WORKLOADS
    27.
    发明公开

    公开(公告)号:US20240111511A1

    公开(公告)日:2024-04-04

    申请号:US17936957

    申请日:2022-09-30

    CPC classification number: G06F8/65 G06F9/4843

    Abstract: A computer implemented method, apparatus, system, and computer program product manages updates to images. A computer system determines shared layers present between the images selected for update management. The images comprise executable code that are run to create containers. The computer system detects a change in a shared layer in the shared layers for an image in the images. The computer system updates the shared layer in the shared layers in a set of the images having the shared layer in response to detecting the change to the shared layer for the image. According to other illustrative embodiments, a computer system and a computer program product for managing updates to images are provided.

    INTELLIGENTLY SCALING DATABASE AS A SERVICE RESOURCES IN A CLOUD PLATFORM

    公开(公告)号:US20240103896A1

    公开(公告)日:2024-03-28

    申请号:US17952244

    申请日:2022-09-24

    Abstract: A computer-implemented method, system and computer program product for scaling a resource of a Database as a Service (DBaaS) cluster in a cloud platform. User service requests from a service cluster to be processed by the DBaaS cluster are received. A first set of tracing data is generated by a service mesh, which facilitates service-to-service communication between the service cluster and the DBaaS cluster, from the user service requests. A second set of tracing data is generated by the DBaaS cluster from handling the user service requests. A dependency tree is then generated to discover application relationships to identify potential bottlenecks in nodes of the DBaaS cluster based on these sets of tracing data. The pod(s) of a DBaaS node are then scaled based on the dependency tree, which is used in part, to predict the utilization of the resources of the DBaaS node identified as being a potential bottleneck.

Patent Agency Ranking