Distributed Storage Encoding With XOR Matrices and Bitonic Decoding
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Solution Overview
Problem
Existing encoding and decoding schemes, such as Reed-Solomon codes and MDS codes based on XOR operations, suffer from high computational complexity and storage redundancy, especially as the number of nodes in a network increases.
Innovation Solution
The proposed solution involves an encoding method that divides stored data into information vectors, generates an information matrix based on the number of nodes and vectors, and calculates encoded blocks to reduce computational complexity and storage overhead. The decoding method involves acquiring encoded blocks and connection nodes, generating decoding blocks, and performing bitonic decoding to reduce computational complexity and space overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Reed-Solomon code or MDS code based on XOR operation is used for encoding and decoding, then data protection and redundancy are achieved, but encoding and decoding complexity increases significantly
Solution Approach 1:
The patent replaces complex finite field operations (mechanical/mathematical system) with simpler XOR operations. By constructing encoding and decoding matrices using only XOR operations instead of traditional Reed-Solomon finite field arithmetic, the system achieves the same data protection reliability with significantly reduced computational complexity
Solution Approach 2:
The patent changes the operational parameters of the encoding scheme by using XOR-based matrix operations instead of traditional finite field multiplication and inversion. This parameter change maintains the MDS code properties for data protection while reducing the complexity from O(n^2) finite field operations to O(n^2) simple XOR operations that are computationally much lighter
2Reliability
If the number of nodes in the network increases, then data distribution and reliability improve, but storage redundancy increases significantly
Solution Approach 1:
The patent segments the storage system into k information blocks distributed across n nodes, where each node stores exactly one encoded block. This segmentation ensures that storage redundancy is minimized by storing only the necessary encoded data without additional overhead, while maintaining reliability through the distributed nature of the segmentation across multiple nodes
3Reliability
If traditional encoding schemes are used, then data protection is achieved, but space overhead for encoding and decoding increases
Solution Approach 1:
The patent uses systematic encoding where the first k nodes store exact copies of the original information blocks. This copying approach eliminates the need for complex reconstruction overhead and reduces space requirements compared to non-systematic schemes, as the original data is directly accessible from these nodes without requiring full decoding operations
Data Source
AI summary
An encoding method, a decoding method, an electronic device and a storage medium are disclosed. The encoding method includes: acquiring stored data in a storage system, and acquiring nodes corresponding to the stored data to obtain a number of the nodes; dividing the acquired stored data into a sequence of information vectors, and generating an information matrix according to the number of the nodes and a number of the sequence of information vectors; and calculating an encoded block according to each information vector and the information matrix to obtain a sequence of encoded blocks.