SeigrCluster

SeigrCluster in the Seigr Ecosystem

The SeigrCluster is a logical grouping of .seigr capsules within the Seigr Urcelial-net. It is designed to manage large datasets in modular segments, supporting efficient storage, retrieval, and scalability. Each SeigrCluster operates as a decentralized structure of capsules, linked by unique hashes and governed by adaptive replication policies to ensure resilience, accessibility, and fault tolerance.

Purpose of SeigrCluster

SeigrCluster organizes and connects capsules in a way that supports Seigr's modular, distributed data ecosystem. The primary objectives of SeigrCluster are:

• Modular Data Segmentation: Divides large data into manageable .seigr segments that can be independently stored, accessed, and replicated across nodes.
• Adaptive Replication and Scalability: Implements Adaptive Replication strategies to optimize resource allocation based on capsule access frequency.
• Fault Tolerance and Recovery: Facilitates recovery of lost or corrupted capsules by providing a multi-path retrieval structure across connected capsules.
• Efficient Retrieval Pathways: Allows Seigr to organize and access capsules efficiently through Multi-Path Retrieval, improving data availability and response times.

Structure of SeigrCluster

The SeigrCluster is defined by the following core components, which are managed using Protocol Buffers for efficient data serialization, ensuring schema consistency and interoperability:

• Cluster Metadata: Stores global metadata for the cluster, including creator ID, root hash, and the total number of segments.
• Capsule Links and Hashes: Each capsule within the cluster is assigned a primary hash and secondary links, creating flexible pathways for retrieval.
• Replication Parameters: Defines replication frequency and demand-based adjustments, allowing clusters to optimize their storage and retrieval based on network conditions.
• Access Context: Records information about data access patterns to guide replication and retrieval strategies, integrating with Seigr's Access Context module.

SeigrCluster Protocol Buffer Schema

SeigrCluster is defined using Protocol Buffers, allowing structured, efficient representation and manipulation across Seigr's decentralized network. The schema below represents a typical SeigrCluster structure:

syntax = "proto3";

message SeigrCluster {
    string root_hash = 1;                // Root hash for cluster identification
    string creator_id = 2;               // ID of the original creator of the cluster
    int32 total_segments = 3;            // Total number of capsules within the cluster
    repeated Capsule segments = 4;       // Capsules in the cluster
    repeated string secondary_clusters = 5; // Paths to secondary clusters if needed
    AccessContext access_context = 6;    // Access-related metadata for adaptive scaling

    message Capsule {
        int32 index = 1;                 // Segment index for accurate reassembly
        string hash = 2;                 // Unique hash identifier for each capsule
        int32 threat_level = 3;          // Threat level for adaptive replication
    }
}

Field Definitions

The main fields of SeigrCluster are designed to capture both global cluster metadata and details about individual capsules within the cluster.

• root_hash: The root identifier of the cluster, used to distinguish this cluster in the Seigr network.
• creator_id: Unique ID of the original creator, establishing the cluster's ownership and accountability.
• total_segments: Indicates the number of .seigr capsules (or segments) in the cluster, ensuring accurate capsule reassembly.
• segments: A list of capsules in the cluster, each defined by an index, a unique hash, and a threat level that informs adaptive replication.
• secondary_clusters: Links to secondary clusters, used if the primary cluster exceeds storage capacity, ensuring efficient scaling.
• access_context: Metadata from the Access Context, providing access patterns that help Seigr adjust replication and retrieval priorities.

Core Components and Functionality

The SeigrCluster component incorporates several critical features, each supporting the decentralized, adaptable nature of Seigr’s data management approach:

Capsule

The Capsule message is a sub-structure within SeigrCluster, representing individual .seigr capsules. Each capsule’s entry includes:

• index: Numeric index representing the capsule's order, ensuring segments are assembled in the correct sequence.
• hash: Unique hash generated using HyphaCrypt to uniquely identify and verify each capsule.
• threat_level: The threat level of each capsule, determined by the Immune System, which impacts the capsule’s replication frequency. Higher threat levels lead to more frequent replication across nodes for security.

Access Context

The AccessContext field holds access-related metadata, integrating with the Access Context module. This metadata enables the cluster to adjust replication and retrieval patterns based on capsule demand and network conditions. Key access context attributes include:

• access_count: Tracks how frequently a capsule is accessed, influencing replication frequency and retrieval priority.
• last_accessed: Records the last access timestamp, helping Seigr prioritize recently accessed capsules in the Adaptive Replication strategy.

Adaptive Replication and SeigrCluster

The SeigrCluster integrates tightly with Seigr’s Adaptive Replication model. Based on factors such as access frequency, network congestion, and threat level, capsules within a cluster are dynamically replicated:

• Demand Scaling: Capsules with higher access frequencies trigger increased replication, ensuring high-demand data remains readily available across the network.
• Adaptive Retrieval Paths: Capsules with multiple retrieval pathways use Seigr’s Multi-Path Retrieval model, selecting the optimal path based on current network performance and response times.
• Self-Healing Mechanism: In response to detected faults, corrupted capsules are reconstructed from alternative paths, leveraging SeigrCluster’s distributed redundancy.

Integration with the Immune System

SeigrCluster works closely with Seigr’s Immune System to ensure data integrity and resilience. The Immune System uses SeigrCluster metadata to monitor and manage capsules, responding to security threats and performance degradation by initiating adaptive replication, alerting on tampering, or rolling back to a previous, verified state if needed.

• Threat-Based Replication Adjustment: Capsules with elevated threat levels prompt the Immune System to trigger frequent replication across more nodes, ensuring that critical or at-risk data remains secure.
• Integrity Verification: The Immune System uses SeigrCluster’s hash data to verify capsule integrity and identify tampered or corrupted capsules for possible rollback.
• Cross-Node Validation: By cross-validating capsule integrity across multiple nodes, SeigrCluster contributes to robust fault tolerance and data availability.

Fault Tolerance Model in SeigrCluster

SeigrCluster’s architecture supports fault tolerance through distributed redundancy and cross-node validation. For a capsule replicated across $k$ nodes with a probability $p$ that each node remains intact, the probability that the capsule remains accessible, $P_{\text{accessible}}$, is given by:

$P_{\text{accessible}}=1-(1-p)^{k}$

This model demonstrates that increasing the number of replicas enhances the availability of the capsule, supporting SeigrCluster’s resilience against node failure and network interruptions.

Example SeigrCluster Scenario

Consider a scenario where a data file is divided into five .seigr capsules within a SeigrCluster. Each capsule is assigned an index (0 to 4) and unique hash:

1. Creation and Initial Replication: A data file is divided into capsules, each receiving an initial replication based on network conditions and access context. 2. Access Frequency Triggers Replication: Capsule 2, accessed frequently, prompts SeigrCluster to increase its replication across additional nodes, ensuring availability. 3. Integrity Check and Rollback: The Immune System detects a fault in Capsule 3 and initiates a rollback to its previous, verified state, maintaining data accuracy. 4. Dynamic Scaling: As network demand shifts, SeigrCluster adjusts replication and retrieval paths, optimizing resource usage while preserving accessibility.

Future Enhancements and Extensions

Potential future developments for SeigrCluster include:

• Cross-Cluster Coordination: Enhancing data relationships between clusters, allowing capsules to share context and adapt collectively to network conditions.
• Predictive Replication: Leveraging predictive algorithms to adjust replication based on anticipated demand patterns, enhancing data availability for high-use capsules.
• Federated Clustering: Supporting multi-cluster setups that span decentralized nodes and allow independent clusters to coordinate on shared data resources.

Conclusion

The SeigrCluster structure is a foundational element of Seigr’s modular and decentralized data management model. By supporting adaptive replication, secure access, and resilient retrieval, SeigrCluster enables Seigr capsules to adapt to evolving network conditions and usage patterns. As a core component of the Seigr ecosystem, SeigrCluster exemplifies Seigr’s commitment to scalable, secure, and ethically managed data.

For more information, refer to:

• Adaptive Replication
• Access Context
• Immune System
• Multi-Path Retrieval
• HyphaCrypt
• Protocol Buffers
• Seigr Metadata