Encoder Decoder Module

Encoder/Decoder Module

The Encoder/Decoder Module is a core component of Seigr's data ecosystem, responsible for transforming raw data into the .seigr file format and reassembling .seigr segments into their original form. This module supports Seigr’s modular, decentralized data approach by segmenting data, encoding it in senary (base-6) format, and enabling flexible, secure data retrieval. With robust features for demand-based replication, multi-path decoding, and adaptive scalability, the Encoder/Decoder Module is essential to Seigr's dynamic data structure.

This module is divided into two main classes:

• SeigrEncoder: Transforms raw data into .seigr capsules.
• SeigrDecoder: Reassembles .seigr segments back into the original file.

Overview

The Encoder/Decoder Module operates at the core of Seigr’s adaptive replication system, integrating HyphaCrypt encryption, Protocol Buffers serialization, and Seigr’s Immune System to protect and manage data across distributed nodes.

The Encoder/Decoder Module is built upon these functionalities:

• Senary Encoding: A compact encoding scheme based on base-6, optimizing storage efficiency.
• Modular Data Segmentation: Segments data into fixed-size capsules, allowing for scalable, distributed storage.
• Adaptive Decoding and Reassembly: Supports multi-path, demand-driven reassembly.
• Protocol Buffers Integration: Serialized metadata ensures compatibility, backward support, and schema evolution.

Encoding Process

The encoding process, handled by the SeigrEncoder class, transforms raw data into senary-encoded, modular capsules (or .seigr files). Each capsule includes metadata, cryptographic hashes, and parameters for adaptive replication. This process is designed for efficiency, traceability, and ease of storage within Seigr’s decentralized architecture.

1. Data Segmentation

The raw input data is divided into fixed-size segments as per the defined TARGET_BINARY_SEGMENT_SIZE in the Seigr protocol, typically set at 53,194 bytes to allow space for metadata while optimizing network transfer.

• Segment Size Determination: The SeigrEncoder segments data according to TARGET_BINARY_SEGMENT_SIZE, generating manageable chunks.
• Hashing for Uniqueness: Each segment is hashed with HyphaCrypt to create a primary hash identifier.
• Senary Conversion: Segments are encoded into senary format via Encoding Utilities, which helps conserve space.

2. Metadata Generation

Each segment receives unique metadata, following the Seigr Metadata schema, which enables traceability, consistency, and adaptability:

• Primary and Secondary Hash Links: Each segment contains primary and secondary hash links, which support multi-path retrieval and redundancy.
• 4D Coordinate Indexing: The capsules carry temporal and spatial coordinates within a four-dimensional grid for advanced data structure navigation.
• Temporal Layers: For historical tracking and rollback support, each capsule maintains a TemporalLayer, which records data snapshots.
• Demand-Based Replication Parameters: Metadata includes adaptive replication settings to dynamically adjust replication frequency based on access.

3. Protocol Buffers Serialization

Metadata is serialized using Protocol Buffers, which allow efficient, schema-driven serialization. Additionally, CBOR (Concise Binary Object Representation) provides secondary compression where required.

• Metadata Serialization: Serialized with Protocol Buffers, ensuring uniform schema.
• CBOR Compression: Adds further compression for capsules that don’t require human readability.
• Backward Compatibility: Ensures capsules remain compatible as protocol versions evolve.

4. Senary Encoding with Adaptive Error Handling

Senary encoding (base-6) is applied for efficient storage, while adaptive error handling maintains data integrity under network fluctuations:

• Error Checking and Redundancy: Each segment undergoes checksum validation and redundancy checks.
• Adaptive Error Recovery: Capsules incorporate error-recovery mechanisms to handle senary encoding errors.
• Integration with the Immune System: Logs failures and activates replication or rollback when necessary.

Decoding Process

The decoding process is managed by the SeigrDecoder class. This process reassembles .seigr segments into their original data form by navigating multi-path structures, verifying integrity, and ensuring accurate reassembly.

1. Segment Retrieval

The SeigrDecoder retrieves encoded segments from storage, verifying their availability and integrity:

• Cluster Files Parsing: Each .seigr file, organized in cluster files, is parsed for continuity.
• Multi-Path Access: Capsules use primary and secondary hashes to locate segments across nodes.
• Adaptive Retrieval Paths: High-demand segments are accessed from nodes with the lowest latency.

2. Integrity Verification

The Integrity Module verifies segment integrity, recomputing and cross-validating each primary hash:

• Hash Verification: Primary hashes are re-validated to confirm segment integrity.
• Layered Integrity Checking: Capsules with multiple Temporal Layers undergo multi-layer integrity checks.
• Cross-Node Validation: Validates data consistency across multiple node replicas.

3. Senary Decoding

Each segment is decoded from senary to binary format, with additional error correction where necessary:

• Base-6 to Binary Conversion: Decodes senary data back into binary format.
• Redundant Error Correction: Applies error correction for high-fidelity data recovery.
• Hybrid Decoding: Decompresses CBOR-encoded capsules where applicable.

4. Segment Reassembly

Segments are reassembled in the original sequence using metadata indices, supporting multi-threaded reassembly for efficiency:

• Ordered Assembly: Ensures correct sequence in reassembly using metadata.
• Multi-Threaded Reassembly: Handles large data sets in parallel.
• Integrity Logging: Logs decoded segments for historical validation.

Adaptive Replication and Demand Scaling

The Encoder/Decoder Module is integrated with Seigr’s adaptive replication strategy, which scales replication based on demand.

• Replication Triggers: Segments with high demand are prioritized for replication.
• Self-Healing and Rollback: Corrupted segments are rebuilt from backup paths or rolled back to historical states.
• Demand-Based Decoding Optimization: Frequently accessed segments are prioritized in decoding.

Security and Integrity Protocols

The module includes robust security and integrity protocols, utilizing HyphaCrypt encryption and Immune System monitoring.

• Encryption with HyphaCrypt: Each segment is encrypted for secure storage.
• Multi-Temporal Integrity Checks: Validates data across multiple Temporal Layers.
• Immune System Integration: Continuously monitors segments and triggers replication or rollback as needed.

Performance and Efficiency

Optimized for high performance, the module minimizes storage requirements and scales across nodes efficiently.

• Parallel Processing: Multi-threaded encoding and decoding reduce processing time.
• Adaptive Demand Scaling: Capsules dynamically adjust replication based on network demand.
• Efficient Metadata Management: Uses Protocol Buffers and CBOR for minimal metadata footprint.

Conclusion

The Encoder/Decoder Module is vital for Seigr’s decentralized architecture, ensuring data integrity, adaptive replication, and efficient reassembly. Through advanced encoding techniques, multi-path decoding, and stringent integrity protocols, this module exemplifies Seigr’s approach to ethical, scalable data management.

For further technical exploration, refer to:

• Seigr Metadata
• Temporal Layering
• Adaptive Replication
• Immune System
• Senary Encoding
• Protocol Buffers
• HyphaCrypt
• Integrity Module
• Encoding Utilities
• Decoding Utilities
• Cluster Files