Heuristic Backup Scheduling for RPO and RTO Compliance
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Solution Overview
Problem
In data protection environments, the complexity of meeting recovery point object (RPO) and recovery time objective (RTO) metrics through asset backup scheduling leads to increased infrastructure and operational complexity, necessitating an efficient method for generating asset backup scheduling plans that consider backup device limitations, RPO violation minimization, and asset prioritization.
Innovation Solution
A heuristic method for generating asset backup scheduling plans involves selecting a backup device, identifying assets, initializing a scheduling plan, generating a backup priority list, iteratively selecting a target asset, identifying and inserting best-fit backup scheduling options, and updating the priority list to optimize backup operations based on RPO and RTO constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional backup scheduling methods are used to meet RPO and RTO metrics, then data protection service levels are maintained, but infrastructure and operational complexity increase
Solution Approach 1:
The patent transforms the backup scheduling problem from a complex constraint satisfaction problem into a simpler optimization problem by changing the approach parameters. Instead of directly managing multiple constraints (RPO, RTO, bandwidth, dependencies), the system uses a score-based evaluation mechanism where each asset receives a priority score based on its backup urgency and characteristics. This parameter transformation simplifies the scheduling decision-making process while maintaining service level compliance.
Solution Approach 2:
The patent segments the backup scheduling process into distinct phases: asset evaluation, priority scoring, queue management, and execution. By dividing the complex scheduling task into manageable segments, each handled by specific algorithms and data structures (such as priority queues and score calculators), the system reduces operational complexity while ensuring all RPO and RTO requirements are met for different asset classes.
2Reliability
If traditional backup scheduling methods are used to meet RPO and RTO metrics, then data protection service levels are maintained, but operational complexity increases
Solution Approach 1:
The patent implements a self-service backup scheduling system that automatically evaluates assets, calculates priorities, and generates schedules without requiring manual intervention. The system autonomously monitors asset changes, updates priority scores, and adjusts schedules in response to varying conditions, eliminating the need for operators to manually manage complex scheduling constraints while maintaining service level agreements.
Solution Approach 2:
The patent incorporates continuous feedback mechanisms where the system monitors backup execution results, asset changes, and performance metrics, then uses this feedback to dynamically adjust priority scores and schedule adjustments. This closed-loop control simplifies operations by allowing the system to self-correct and adapt to changing conditions without manual reconfiguration, while ensuring RPO and RTO compliance is maintained.
3Productivity
If priority-based iterative scheduling is implemented, then scheduling efficiency is improved, but computational requirements increase
Solution Approach 1:
The patent applies partial action by focusing computational resources on evaluating and scheduling only the most critical assets first, rather than processing all assets uniformly. The priority scoring mechanism identifies a subset of high-priority assets that require immediate attention, allowing the system to achieve effective scheduling results without performing exhaustive evaluations of every single asset, thus reducing overall computational requirements while maintaining scheduling efficiency.
Data Source
AI summary
An efficient method for generating asset backup scheduling plans. Within a data protection environment, at least two service level metrics may be observed—a recovery point object (RPO) and a recovery time objective (RTO). In order to meet acceptable values for these metrics, on par with established service level agreements, infrastructure employed throughout the data protection environment, as well as the scheduling of asset backup operations, tend to grow in complexity. To address service distributions potentially emerging from the aforementioned complexities, the disclosed method proposes a heuristic approach to generating asset backup scheduling plans, which consider factors such as backup device limitations, RPO violation minimization, asset usage, and asset prioritization.