Application-Aware Disaster Recovery via Delta Backup
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Solution Overview
Problem
Current data backup and disaster recovery methods consume significant network bandwidth and resources, often requiring all or nothing approaches, which is inefficient and may not prioritize critical applications during recovery.
Innovation Solution
A computer system preloads data images, chunks them into hash-represented chunks, and generates a logical backup representation including delta data, allowing efficient data restoration using hash values and delta data, while defining a disaster recovery policy to prioritize which applications are restored after a disaster.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data is backed up using traditional backup methods, then complete data recovery is ensured, but network bandwidth consumption increases significantly
Solution Approach 1:
The patent extracts and transmits only the differential portions of data that have changed since the last backup, rather than transmitting entire data sets. This selective extraction of changed blocks significantly reduces network bandwidth consumption while ensuring complete recoverability of all data including both changed and unchanged portions.
Solution Approach 2:
The backup system segments data into manageable blocks or chunks, allowing individual blocks to be identified, tracked, and transmitted independently. This segmentation enables the system to identify only the specific blocks that have changed and transmit only those, rather than treating the entire data set as a single unit that requires full transmission.
2Reliability
If complete data backup is performed, then full disaster recovery capability is achieved, but storage resources are consumed inefficiently
Solution Approach 1:
The system extracts and stores only the differential portions of data that have changed since the last backup point. By storing only these differential blocks rather than complete data copies, the system achieves full disaster recovery capability while consuming significantly fewer storage resources.
Solution Approach 2:
The backup system implements a nested structure where differential backup data is stored within the context of the base backup image. The differential blocks are nested within or associated with the parent image, allowing the system to reconstruct complete data by combining the base image with the nested differential portions, thereby reducing overall storage requirements.
3Reliability
If traditional all-or-nothing disaster recovery is implemented, then complete system restoration is ensured, but recovery time increases
Solution Approach 1:
The system applies partial action by restoring only the specific differential portions of data that have changed, rather than restoring complete data sets. This allows for selective recovery of only the necessary changes, significantly reducing recovery time while ensuring that all required data including both base and differential portions are restored completely.
Solution Approach 2:
By segmenting the recovery process into base image restoration and differential block application, the system can restore the base system quickly and then apply only the necessary differential changes. This segmented approach to recovery reduces overall recovery time compared to traditional methods that require complete data set restoration.
4Adaptability or versatility
If fine-grained data restoration is enabled, then selective recovery of specific applications is possible, but system complexity increases
Solution Approach 1:
The system segments data into blocks with associated metadata that identifies the application or software associated with each block. This segmentation enables selective recovery by allowing the system to identify and restore only the blocks associated with specific applications, providing fine-grained control over recovery while managing complexity through automated metadata-based identification.
Solution Approach 2:
The backup system implements feedback mechanisms that track which applications or software are associated with specific data blocks. This feedback information is used to enable selective recovery capabilities, allowing users to restore only the data associated with specific applications. The automated tracking and identification through feedback reduces the complexity burden on the user.
Data Source
AI summary
A computer program product for implementing a method for performing a scoped data recovery, the computer program product comprising one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by one or more processors of the computing system, cause the computing system to perform the method, the method comprising: an act of defining a disaster recovery policy that specifies which software applications among a plurality of different software applications is to be restored after a disastrous event has occurred; an act of receiving, from a generated virtual hard disk, difference data comprising data differences between data received from a user and one or more preloaded data images, the virtual hard disk being configured to receive the difference data from the user; an act of determining, based on the disaster recovery policy, which software application's data is to be restored; and an act of restoring the software application delta data to the user according to the policy.