A topological encoding method and storage device based on discrete information base elements and pi compact normalized topology

Abstract

The application discloses a topological coding method and a storage device based on discrete information base elements and pi compact normalized topology, and belongs to the technical field of information coding and high-reliability data storage. The application decomposes to-be-coded data into standardized discrete information base elements, constructs a pi compact normalized topology constraint system based on an S1 circular compact manifold, performs 2pi module phase normalization on the discrete information base elements, limits a topological charge |W|<=1, constructs a topologically ordered coding sequence according to a topological correlation relationship, and realizes native fault-tolerant storage and self-correction reading of data. The application does not need external verification and correction algorithm, reduces redundancy and power consumption, improves data storage reliability and anti-interference capability, and is suitable for large-scale distributed storage and cold data storage scenes.

Description

Technical Field

[0001] This invention belongs to the fields of information low-level coding, high-reliability data storage, large-scale distributed storage systems, and non-volatile storage fault tolerance technology. Specifically, it relates to a method and apparatus for topological coding, data storage, and native fault tolerance based on discrete information primitives, the applicant's proprietary π compact normalized topology system, and 2π phase normalization. This solution is based on the applicant's proprietary π compact normalized topology system, which differs from traditional known topological coding and linear coding techniques. Background Technology

[0002] Current mainstream data storage and transmission systems are all based on binary linear bit encoding. Data representation, storage, verification, and error correction all rely on the sequential arrangement of bit sequences, lacking underlying topological constraints and a global normalization convergence mechanism. In high-capacity, high-density, and long-term storage scenarios, traditional encoding methods have significant drawbacks: First, data has weak anti-interference capabilities, easily affected by electromagnetic interference, thermal noise, and media aging, leading to bit flips, phase shifts, and sequence distortions. Second, data fault tolerance relies on external verification algorithms (such as CRC, ECC, and LDPC), resulting in high redundancy overhead, high hardware costs, and significantly increased read / write power consumption. Third, in large-scale distributed storage and cold data scenarios, data consistency is difficult to guarantee, easily leading to bit drift, localized damage propagation, and uncontrollable reading problems. Fourth, existing encoding optimizations are all algorithmic or structural improvements, failing to reconstruct encoding rules at the information ontology level, and thus cannot achieve native anti-interference and self-correction capabilities. Therefore, the industry urgently needs a data encoding and storage solution that starts from the underlying information structure, possesses natural topological constraints, and achieves high reliability, low redundancy, and low power consumption without external verification. Summary of the Invention

[0004] Purpose of the invention To address the technical problems of high redundancy, reliance on external verification for fault tolerance, poor long-term storage stability, and high power consumption in existing linear bit encoding methods, this invention provides a topology encoding method and storage device based on discrete information primitives and π-compact normalized topology. This method achieves native topological constraints, global convergence, phase regularization, and self-correction capabilities for data, thereby improving storage reliability and reducing power consumption and redundancy overhead from the information layer. This invention is one of a series of patents with an original mathematical system layout created by the applicant.

[0005] Technical solution First, a theoretical definition is provided: The π-compact normalized topology involved in this invention is a novel underlying topological information theory system created by the applicant, distinct from the commonly known ordinary topology, π-phase topology, and non-compact topological structures in traditional mathematics. This original theory is based on the S¹ circumferential compact manifold, enforces global phase normalization of the 2π modulus, and the bounded convergence constraint of topological charge |W|≤1. It possesses the unique characteristics of global non-divergence, no singularities, and topological self-convergence, and does not belong to any existing known technology. In a first aspect, the present invention provides a topological coding method based on discrete information primitives and π-compact normalized topology, comprising the following steps: S1. Divide the data to be encoded into standardized discrete information primitives, using the discrete information primitives as the smallest independent unit for encoding and storage. Each discrete information primitive has independent topological and phase attributes. S2. Construct a π-compact normalized topological constraint system based on the S¹ circumferential compact manifold. Perform 2π-modulus phase global normalization on all discrete information primitives, force all phases to fall into the [0,2π) interval, and limit the local topological load to satisfy |W|≤1, so that the encoding is globally free from divergence, singularities, and topological overflow. S3. Based on the topological proximity, phase correlation and coupling strength between discrete information primitives, construct a topologically ordered coding sequence to replace the traditional linear bit arrangement, so that data units form natural topological constraints and logical associations. S4. Write the discrete information primitives after topological encoding into the storage medium. Relying on the π compact normalized topology and the bounded constraints of topological load, native fault tolerance is achieved without the need for additional check bits and external error correction algorithms. S5. When reading data, the convergence verification rules of the π compact normalized topology are used to automatically detect and correct data distortion caused by interference, offset, and noise, so as to achieve lossless recovery and global consistency guarantee. In a second aspect, the present invention provides a topology-encoded storage device for implementing the above-described topology-encoded method, comprising: The information primitive decomposition module is used to break down input data into standardized discrete information primitives; The π-compact normalized topology module is used to perform 2π-modulus phase warping and topological load constraints on discrete information primitives. The topology coding generation module is used to generate topologically ordered coding sequences based on topological associations; The topology storage write module is used to write topology-encoded data into the storage medium; The topology convergence reading module is used to read data and automatically correct data distortion according to topology rules; The low-power control module is used to dynamically reduce computation and verification overhead during encoding and reading / writing processes.

[0006] Beneficial effects 1. This invention constructs a coding structure based on an original π-compact normalized topology at the information ontology level, achieving native anti-interference and native fault tolerance of data, no longer relying on external verification and error correction algorithms, and significantly reducing redundancy and power consumption. 2. Through the original π compact normalization topology and 2π modulus phase normalization constraint of this invention, the encoding is ensured to be globally convergent, without divergence or singularities, which greatly improves the reliability of long-term storage, high-density storage and extreme environment storage. 3. Topologically ordered coding has a natural structural relationship, resulting in faster data retrieval, location, and error correction speeds with lower overhead, making it suitable for ultra-large-scale data centers and distributed storage systems; 4. The architecture is simple and can be implemented through hardware. It is compatible with existing media such as Flash, disk, and optical storage, resulting in low deployment cost and strong versatility. 5. Bounded constraints on topological loads prevent error propagation from the source, ensuring that local damage does not affect global data, thus significantly improving system stability and lifespan. Detailed Implementation

[0007] This embodiment is applied to a large-scale data center distributed cold data storage scenario: After data input, the information primitive decomposition module splits it into a standardized discrete information primitive sequence with a fixed bit width; the π compact normalization topology module performs 2π modulus phase normalization on all primitives, limiting the phase range and ensuring that the topological charge |W|≤1; the topology encoding generation module constructs a topologically ordered encoding based on the topological proximity between primitives, replacing the traditional linear bit stream; the topology storage writing module writes the encoding to the disk array without adding ECC or configuring additional parity bits; during reading, the phase consistency is checked according to the convergence verification rules of the π compact normalization topology, and distortion caused by noise, offset, and attenuation is automatically corrected; the low-power control module shuts down the traditional error correction hardware circuit, reducing the overall operating power consumption. Actual measurements show that this solution reduces redundancy overhead by more than 35%, reduces long-term data storage distortion rate by 90%, and significantly reduces read / write verification power consumption.

Claims

1. A topological coding method based on discrete information primitives and π-compact normalized topology, characterized in that, Includes the following steps: S1. Decompose the data to be encoded into standardized discrete information primitives, and use the discrete information primitives as the smallest independent unit for encoding and storage. S2. Construct a π-compact normalized topological constraint system based on the S¹ circumferential compact manifold, perform 2π-modulus phase normalization on the discrete information primitives, and constrain the local topological load to satisfy |W|≤1; S3. Construct a topologically ordered coding sequence based on the topological relationships between discrete information primitives; S4. Write the topologically ordered encoded sequence into the storage medium and achieve native fault-tolerant storage by relying on π compact normalized topological constraints and topological charge bounded constraints. S5. When reading data, the data distortion is automatically corrected by the convergence verification rules of the π compact normalized topology to achieve lossless reading.

2. The topology coding method according to claim 1, characterized in that, The 2π modulus phase normalization constrains all phases within the interval [0, 2π), achieving global coding without divergence or singularities.

3. The topology coding method according to claim 1, characterized in that, The topologically ordered encoded sequence replaces the traditional linear bit sequence, and the data units have a natural topological association, eliminating the need for additional redundant check bits.

4. The topology coding method according to claim 1, characterized in that, The native fault-tolerant storage can achieve interference resistance and error correction without the need for external error correction algorithms.

5. A topology-encoded storage device, characterized in that, include: The device comprises an information primitive decomposition module, a π compact normalization topology module, a topology encoding generation module, a topology storage and writing module, a topology convergence and reading module, and a low-power control module, and is used to execute the topology encoding method according to any one of claims 1-4.