US 2025/0094875 A1Published application

Configuring Autosave Triggers Based On Value Metrics

AssigneeOracle International Corporation

InventorsSatish Chandra Oruganti, Shreyas Ravindranath, Ganesh Kumar Gupta, Michael Patrick Rodgers

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Abstract

Techniques for configuring autosave triggers in a computing environment based on environment and data conditions are disclosed. A system trains a machine learning model based on data attributes and environmental attributes to generate autosave value triggers for a computing environment. The autosave value triggers are triggered by different conditions. For example, one autosave trigger may be triggered when an error condition is detected. Another may be triggered when a certain number of operations are performed. The machine learning model generates autosave trigger values scores for one or more autosave triggers. The system may implement the autosave triggers in the computing environment based on the autosave trigger values.

Claims20

Dependent claims

One or more non-transitory computer readable media comprising instructions that, when executed by one or more hardware processors, causes performance of operations comprising:

storing, by a computing system comprising first memory and second memory, a set of rules for initiating autosave operations, wherein the first memory does not retain stored data upon losing power to the first memory, and wherein the second memory retains stored data upon losing power to the second memory;
monitoring, in real-time, conditions in the computing system;
based on monitoring the conditions in the computing system, detecting a first autosave trigger condition specified in the set of rules, wherein the first autosave trigger condition comprises at least one of:
an error-based autosave that:
(1) detects an error, (2) identifies a state of data immediately prior to the error, and (3) saves the state of the data immediately prior to the error;
an idle-time autosave that saves the data based on detecting an idle state of a program accessing the data;
a focus-based autosave that saves the data based on detecting a change of focus from one application displayed on a graphical user interface (GUI) to another application displayed on the GUI;
an operations-based autosave that saves the data based on detecting performance of a predetermined number of operations;
an environment-based autosave that saves the data based on detecting at least one of:
a power fluctuation;
a threshold temperature;
a threshold memory usage value;
a threshold latency value;
and
based on detecting the first autosave trigger condition specified in the set of rules:
identifying a first data set stored in the first memory;
and
storing the first data set in the second memory.

15 more elements

A method, comprising:

storing, by a computing system comprising first memory and second memory, a set of rules for initiating autosave operations, wherein the first memory does not retain stored data upon losing power to the first memory, and wherein the second memory retains stored data upon losing power to the second memory;
monitoring, in real-time, conditions in the computing system;
based on monitoring the conditions in the computing system, detecting a first autosave trigger condition specified in the set of rules, wherein the first autosave trigger condition comprises at least one of:
an error-based autosave that:
(1) detects an error, (2) identifies a state of data immediately prior to the error, and (3) saves the state of the data immediately prior to the error;
an idle-time autosave that saves the data based on detecting an idle state of a program accessing the data;
a focus-based autosave that saves the data based on detecting a change of focus from one application displayed on a graphical user interface (GUI) to another application displayed on the GUI;
an operations-based autosave that saves the data based on detecting performance of a predetermined number of operations;
an environment-based autosave that saves the data based on detecting at least one of:
a power fluctuation;
a threshold temperature;
a threshold memory usage value;
a threshold latency value;
and
based on detecting the first autosave trigger condition specified in the set of rules:
identifying a first data set stored in the first memory;
and
storing the first data set in the second memory.

15 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/967,007Filed 3 Dec 2024
Priority: 13 May 2021
Published: 20 Mar 2025
Term ends: Not estimatedThe source records don’t support an estimate.

Classification10 codes

G06F 18/28
Analysing: determining representative reference patterns, e.g. by averaging or distorting; Generating dictionaries
G06N 20/00
Machine learning
G06F 11/1438
At system level: restarting or rejuvenating
G06F 11/1446
Error detection or correction of the data by redundancy in operations: point-in-time backing up or restoration of persistent data

Family

Application17/319,599Continuation · filed 13 May 2021
Application18/967,007Continuation
US 12,198,024 B2Related patent
US 2022/0366296 A1Published application
US 2025/0094875 A1This patent

From the US filing history. Foreign family members aren’t listed.

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