Polynomial Network Coding for Low-Overhead Decentralized Storage
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Solution Overview
Problem
Existing wireless communication systems, such as 5G NR, face challenges in managing increasing mobile broadband demand, and decentralized data storage systems like IPFS face issues with reliance on centralized nodes, leading to potential data loss and privacy concerns.
Innovation Solution
Implement vector network coding to partition data into coded parts, using cryptographic keys and polynomial functions over finite fields, and store these parts across decentralized networks, ensuring data privacy and reducing storage and bandwidth overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in decentralized networks using traditional methods, then data distribution is achieved, but storage overhead and bandwidth consumption increase
Solution Approach 1:
The patent segments original data into multiple original data parts and applies network coding to generate coded data parts. Each node stores only a portion of the coded data rather than complete replicas, reducing storage overhead while maintaining data availability through distributed reconstruction capabilities.
Solution Approach 2:
The patent transforms data from its original form into coded representations using polynomial functions over finite fields. This parameter transformation enables efficient storage and transmission where coded data parts can be reconstructed into original data through mathematical operations, optimizing the balance between storage efficiency and data recovery reliability.
2Reliability
If cryptographic keys are generated from coded data, then data security is improved, but computational complexity increases
Solution Approach 1:
The patent performs cryptographic key generation as a preliminary action during the data encoding phase. By generating cryptographic keys from coded data parts before distribution, the system establishes security mechanisms in advance, avoiding more complex real-time key derivation operations during data access and reconstruction.
Solution Approach 2:
The patent uses coded data parts as an intermediary between original data and cryptographic keys. Instead of directly deriving keys from original data or using separate key management systems, the coded representations serve as the basis for key generation, simplifying the overall computational process while maintaining security.
3Reliability
If polynomial network coding is used to encode data, then data privacy is enhanced, but encoding and decoding complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where nodes can independently perform encoding and decoding operations using locally stored polynomial coefficients and finite field arithmetic rules. Each node autonomously generates its coded data parts and can participate in reconstruction processes without requiring centralized coordination, reducing overall system complexity despite the mathematical operations involved.
Data Source
AI summary
Vector network coding, such as linear network coding, is used to compute a plurality of coded data parts from original data, wherein each coded data part is computed from a cryptographic hash function of a previous coded data part. A recipient of the coded data parts can compute the cryptographic hash functions of the coded data to reproduce a system of linear equations, which can be solved to recover the original data. A cryptographic key that employs a polynomial over a finite field can have polynomial coefficients that comprise a function of vector network coding coefficients.