公开(公告)号：US12235795B2

公开(公告)日：2025-02-25

申请号：US17816276

申请日：2022-07-29

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Sagar Venkappa Nyamagouda ,  Smitha Jayaram ,  Hiro Rameshlal Lalwani ,  Rachit Gupta ,  Sherine Jacob ,  Anand Andaneppa Ganjihal

IPC: G06F16/13 ,  G06F11/34

Abstract: In some examples, a system receives workload information of a workload collection, and applies a machine learning model on the workload information, the machine learning model trained using training information including features of different types of workloads. The system produces, by the machine learning model, an identification of a first file system from among different types of file systems, the machine learning model producing an output value corresponding to the first file system that is a candidate for use in storing files of the workload collection.

公开(公告)号：US20240037067A1

公开(公告)日：2024-02-01

申请号：US17816276

申请日：2022-07-29

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Sagar Venkappa Nyamagouda ,  Smitha Jayaram ,  Hiro Rameshlal Lalwani ,  Rachit Gupta ,  Sherine Jacob ,  Anand Andaneppa Ganjihal

IPC: G06F16/13 ,  G06F11/34

CPC classification number: G06F16/13 ,  G06F11/3414

Abstract: In some examples, a system receives workload information of a workload collection, and applies a machine learning model on the workload information, the machine learning model trained using training information including features of different types of workloads. The system produces, by the machine learning model, an identification of a first file system from among different types of file systems, the machine learning model producing an output value corresponding to the first file system that is a candidate for use in storing files of the workload collection.

公开(公告)号：US11347702B2

公开(公告)日：2022-05-31

申请号：US17073316

申请日：2020-10-17

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Mohan Govindaraj ,  Ashutosh Kumar ,  V. V. Satyanarayana Reddy N ,  Rachit Gupta

IPC: G06F16/00 ,  G06F16/21 ,  G06F9/455 ,  G06F16/16

Abstract: Examples described herein relate to migrating data in a system having multi-tiered physical storage. In an example, relative weights corresponding to a plurality of data access parameters may be determined based on a ranking associated with each of the plurality of data access parameters. Further, a priority metric corresponding to each of a plurality of candidate types may be determined based on the relative weights of the plurality of data access parameters. Furthermore, one or more candidate types may be selected from the plurality of candidate types based on the priority metric corresponding to each of the plurality of candidate types. Moreover, data containers corresponding to the selected one or more candidate types may be migrated from a first tier storage to a second tier storage.

公开(公告)号：US20210191910A1

公开(公告)日：2021-06-24

申请号：US17073316

申请日：2020-10-17

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Mohan Govindaraj ,  Ashutosh Kumar ,  V. V. Satyanarayana Reddy N ,  Rachit Gupta

IPC: G06F16/21 ,  G06F16/16 ,  G06F9/455

Abstract: Examples described herein relate to migrating data in a system having multi-tiered physical storage. In an example, relative weights corresponding to a plurality of data access parameters may be determined based on a ranking associated with each of the plurality of data access parameters. Further, a priority metric corresponding to each of a plurality of candidate types may be determined based on the relative weights of the plurality of data access parameters. Furthermore, one or more candidate types may be selected from the plurality of candidate types based on the priority metric corresponding to each of the plurality of candidate types. Moreover, data containers corresponding to the selected one or more candidate types may be migrated from a first tier storage to a second tier storage.