Dynamic Backup Path Selection for Data Redundancy
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Solution Overview
Problem
Current data backup systems are vulnerable to corruption, accidental deletion, and data center outages, and they fail to optimize performance and cost effectively for redundant data backup.
Innovation Solution
A system and method for dynamically optimizing redundant backup of data sets by receiving user inputs for backup parameters and threshold limits, comparing current values with these limits, and dynamically switching between direct and secondary storage backup paths to optimize performance and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If direct redundant backup is used from client device to tertiary storage, then backup speed is improved, but egress cost increases
Solution Approach 1:
The patent introduces secondary storage as an intermediary component in the backup architecture. Instead of directly transferring data from client device to tertiary storage, the system uses secondary storage as a intermediate destination. This mediator approach allows the system to optimize between backup speed and egress cost by controlling the data flow path and selecting appropriate backup methods (direct vs. indirect) based on cost thresholds and performance requirements.
2Reliability
If redundant backup is implemented to protect against data loss, then data reliability is improved, but system complexity increases
Solution Approach 1:
The patent implements dynamic backup path selection where the system automatically adjusts the backup methodology (direct or indirect) based on real-time conditions and predefined thresholds. The controller dynamically determines the optimal backup path by comparing egress costs against thresholds and selecting appropriate backup methods, thereby maintaining high data reliability while managing system complexity through automated adaptive decision-making rather than rigid complex architectures.
3Loss of energy
If backup parameter optimization is implemented, then cost-effectiveness is improved, but operational complexity increases
Solution Approach 1:
The system implements self-service optimization where the controller automatically monitors backup parameters, compares them against predefined thresholds, and adjusts backup paths without requiring manual user intervention. The automated mechanism evaluates egress costs, selects optimal backup methods, and manages the entire optimization process independently, thereby improving cost-effectiveness while reducing operational complexity through autonomous decision-making.
Data Source
AI summary
A system for dynamically optimizing redundant backup of one or more data sets of a plurality of data sets from a client device to a tertiary storage is presented. The system includes a user input module, a parameter comparison module, a backup path selector, and a redundant backup module. The system is configured to dynamically switch between two backup paths including: (A) direct redundant backup of the data set from the client device to the tertiary storage, or (B) back up of the data set from the client device to a secondary storage and redundant backup of the data set from the secondary storage to the tertiary storage. A related method is also presented.


