Erasure Coding Data Backup Reducing Storage Space
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Solution Overview
Problem
Current data backup methods lack efficiency and effectiveness in managing and optimizing storage resources, leading to inefficiencies in data redundancy and availability, particularly in distributed storage systems.
Innovation Solution
The system implements a construct for data backup that utilizes a network of storage devices to form backup and redundancy groups, with a backup manager facilitating data distribution and redundancy generation using erasure correcting codes, allowing for efficient data restoration and storage space allocation based on availability and accessibility criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional backup methods are used to ensure data safety, then data protection is achieved, but storage space consumption increases significantly
Solution Approach 1:
The patent segments data into multiple shards distributed across different storage devices. Instead of creating complete duplicate backups, the system divides data into segments and stores them across multiple devices, enabling reconstruction of original data from any sufficient subset of shards. This segmentation approach reduces storage requirements while maintaining data protection through distributed redundancy.
Solution Approach 2:
The system changes the parameter of data representation by applying erasure coding transformations. Original data is transformed into encoded shards where only a subset is needed for reconstruction. This parameter change allows the system to achieve the same data protection level with less total storage space compared to traditional full backup methods.
2Reliability
If complete data copies are stored for backup purposes, then data availability is ensured, but system complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where storage devices automatically participate in the erasure coding process. Devices autonomously generate, store, and manage their shards without requiring complex centralized coordination. The system includes automatic recovery mechanisms that can reconstruct data from available shards without manual intervention, reducing overall system complexity while maintaining high availability.
3Quantity of substance
If distributed storage is implemented to reduce storage requirements, then storage efficiency improves, but data restoration difficulty increases
Solution Approach 1:
The system implements feedback mechanisms through metadata tracking that records the location and status of all data shards. This metadata provides real-time feedback about the distributed data state, enabling the recovery process to efficiently identify which shards are available and how to reconstruct the original data. The feedback system reduces restoration difficulty by providing clear guidance on the distributed storage state.
Data Source
AI summary
In some embodiments, a method for detecting a shared data element comprises providing a first feature of a first data element associated with a first storage device; detecting a second feature of a second data element associated with a second storage device, wherein the second feature is the same as the first feature; challenging the second storage device; receiving a response to the challenge; and determining whether the response is acceptable.