Backup Scheduler Using Data Change Rates

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Solution Overview

Problem

Existing data protection systems struggle to dynamically adjust backup schedules and policies in response to changing data loads, often requiring manual overrides to prevent overload conditions.

Innovation Solution

A data protection system utilizing supervised learning classification processes to modify scheduling and policies based on data change rates, employing a policy level controller to dynamically reschedule or redefine policies in response to current data change metrics.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual overrides are used to adjust backup schedules, then backup policies can be modified to prevent overload, but system complexity and operational burden increase

Engineering Contradiction:

Improvebackup schedule reliabilityVSAvoidscheduling system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The backup scheduler automatically monitors data change rates and adjusts backup schedules without manual intervention. The system self-regulates by detecting when data change rates indicate potential overload conditions and autonomously modifies backup timing or frequency, eliminating the need for manual overrides while maintaining schedule reliability.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system implements continuous monitoring of data change rates as feedback input to the scheduling algorithm. This feedback loop enables the scheduler to dynamically adjust backup schedules based on real-time or near-real-time data change measurements, automatically preventing overload conditions without requiring manual system complexity.

Inventive Principle:

Principle #23Feedback

2Device complexity

If backup schedules are fixed and do not adapt to data change rates, then scheduling simplicity is maintained, but backup targets may experience overload conditions

Engineering Contradiction:

Improvescheduling system complexityVSAvoidbackup target reliability

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The backup scheduler transitions from a static, fixed schedule to a dynamic scheduling system that automatically adjusts backup timing based on measured data change rates. The system adapts its behavior in response to changing data conditions, modifying backup schedules to prevent target overload while maintaining operational simplicity through automation rather than manual complexity.

Inventive Principle:

Principle #15Dynamics

3Reliability

If backup schedules are dynamically adjusted based on data change rates, then backup target overload is prevented, but system complexity increases

Engineering Contradiction:

Improvebackup target reliabilityVSAvoidscheduling system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system employs self-service automation where the scheduler autonomously monitors data change rates and adjusts backup schedules without manual intervention. This automated self-regulation prevents backup target overload while avoiding the complexity of manual override mechanisms, as the system serves itself by making scheduling decisions based on real-time data change measurements.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical scheduling adjustments with an automated computational system that uses data change rate measurements to dynamically adjust backup schedules. This substitution of manual operations with an automated algorithm based on measurable data change parameters prevents target overload while maintaining system simplicity through automation rather than human intervention.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Measurement precision

If manual intervention is required to modify backup policies, then precise control is achieved, but productivity and response time decrease

Engineering Contradiction:

Improvebackup policy control precisionVSAvoidbackup operation productivity

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system uses continuous feedback from data change rate measurements to automatically adjust backup policies with precise control. The scheduler monitors data change rates and responds by modifying backup schedules in real-time or near-real-time, achieving both precise policy control and high productivity through automated response rather than manual intervention.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The backup scheduler performs self-service by automatically monitoring data change rates and adjusting backup policies without manual intervention. This automation maintains precise control over backup operations while significantly improving productivity and response time, as the system independently makes scheduling decisions based on measured data change conditions.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12277033B2System and method to automatically modify backup schedules based on data change rates

Publication Date: 2025.04.15 DELL PROD LP

AI summary

A policy level controller coordinates a scheduling and policy engine using a data change metric to dynamically schedule or re-define policies in response to data change rates in data assets in a current backup session. A supervised learning process trains a model using historical data of backup operations of the system to establish past data change metrics for corresponding backups processing the saveset, and modifies policies dictating the backup schedule by determining a data change rate of received data, as expressed as a number of bytes changed per unit of time. In response to input from backup targets regarding present usage, it then modifies the backup schedule to minimize the impact on backup targets that may be at or close to overload conditions.