Invention Grant
- Patent Title: Auto scaling a distributed predictive analytics system with machine learning
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Application No.: US15822439Application Date: 2017-11-27
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Publication No.: US11481598B2Publication Date: 2022-10-25
- Inventor: Mahadev Khapali , Shashank V. Vagarali
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Cantor Colburn LLC
- Agent Steven Bouknight
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/063 ; G06N3/08

Abstract:
A computer-implemented method for creating an auto-scaled predictive analytics model includes determining, via a processor, whether a queue size of a service master queue is greater than zero. Responsive to determining that the queue size is greater than zero, the processor fetches a count of requests in a plurality of requests in the service master queue and a type for each of the requests. The processor derives a value for time required for each of the requests and retrieves a number of available processing nodes based on the time required for each of the requests. The processor then auto-scales a processing node number responsive to determining that a total execution time for all of the requests in the plurality of requests exceeds a predetermined time value and outputs an auto-scaled predictive analytics model based on the processing node number and queue size.
Public/Granted literature
- US20190164033A1 AUTO SCALING A DISTRIBUTED PREDICTIVE ANALYTICS SYSTEM WITH MACHINE LEARNING Public/Granted day:2019-05-30
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