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Quantum-Secure Dynamic Mesh Ledger (QSDM) is a non-AI, decentralized electronic cash system designed for quantum resistance and hardware-agnostic operation.

NOTE: Current working build is only for Windows OS 10 and above. Linux and macOS versions are in development.

QSDM is developed in phases:

• Phase 1: 2D Mesh Launch
  Focus on stability and manual bootstrapping using libp2p for networking, Proof-of-Entanglement consensus, SQLite with Zstandard compression for storage, and CRYSTALS-Dilithium for quantum-safe cryptography.

• Phase 2: Scalability & Optimization
  Introduces dynamic submeshes, priority-based routing, WASM SDK integration, and ScyllaDB for high throughput.

• Phase 3: 3D Mesh & Self-Healing
  Adds 3D mesh validation, rule-based quarantines, reputation system, and CUDA acceleration.

• Go 1.20 or higher
• SQLite3
• Git

git clone https://github.com/blackbeardONE/QSDM.git
cd QSDM
go mod download
go run cmd/qsdm/main.go

The node will start and initialize libp2p networking. Logs will be written to qsdm.log.

• cmd/qsdm/ - Main application entry point
• pkg/networking/ - libp2p networking setup
• pkg/consensus/ - Proof-of-Entanglement consensus implementation
• pkg/storage/ - SQLite storage with Zstandard compression
• pkg/crypto/ - Quantum-safe cryptography (CRYSTALS-Dilithium)
• config/ - YAML configuration for submesh templates
• internal/logging/ - Logging setup with rotation and levels

See docs/COMPARATIVE_ANALYSIS.md for a detailed comparison of QSDM with Blockchain and DAG technologies.

Below is a flowchart summarizing how the Quantum-Secure Dynamic Mesh Ledger (QSDM) works across its three development phases:

flowchart TD
    subgraph Phase1["Phase 1: 2D Mesh Launch (Stability, Manual Bootstrapping)"]
        P1_Networking["Networking: libp2p (Go)"]
        P1_Consensus["Consensus: Proof-of-Entanglement (PoE)"]
        P1_Storage["Storage: SQLite + Zstandard compression"]
        P1_Cryptography["Cryptography: CRYSTALS-Dilithium"]
        P1_Submesh["Submesh Templates: YAML configs"]
        P1_Workflow["Key Workflow: Manual submesh rules, 2 parent cell validation, compressed storage"]
    end

    subgraph Phase2["Phase 2: Scalability & Optimization (Throughput, Manual Governance)"]
        P2_DynamicSubmeshes["Dynamic Submeshes: Priority-based routing (Go)"]
        P2_WASM["WASM SDK: TinyGo + WASMEdge"]
        P2_Database["Database: ScyllaDB"]
        P2_Governance["Governance: Snapshot-based voting"]
        P2_Workflow["Key Workflow: Voting on submesh rules, priority routing, WASM wallet integration"]
    end

    subgraph Phase3["Phase 3: 3D Mesh & Self-Healing (Autonomy, Security)"]
        P3_3DMesh["3D Mesh: Rust + CUDA (GTX 3050)"]
        P3_Quarantines["Quarantines: Rule-based isolation (Rust)"]
        P3_Reputation["Reputation System: Staked deposits + penalties"]
        P3_Workflow["Key Workflow: Detection of malicious submeshes, CUDA-accelerated validation, reputation penalties"]
    end

    Phase1 --> Phase2 --> Phase3

    Phase1 --> P1_Networking
    Phase1 --> P1_Consensus
    Phase1 --> P1_Storage
    Phase1 --> P1_Cryptography
    Phase1 --> P1_Submesh
    Phase1 --> P1_Workflow

    Phase2 --> P2_DynamicSubmeshes
    Phase2 --> P2_WASM
    Phase2 --> P2_Database
    Phase2 --> P2_Governance
    Phase2 --> P2_Workflow

    Phase3 --> P3_3DMesh
    Phase3 --> P3_Quarantines
    Phase3 --> P3_Reputation
    Phase3 --> P3_Workflow

    subgraph HardwareOptimization["Hardware Optimization"]
        RAM["RAM: 8GB (Phase 1) → 16GB (Phase 2) → 24GB (Phase 3)"]
        GPU["GPU: Parallel hashing → None → CUDA validation"]
        Storage["Storage: SQLite → ScyllaDB → ScyllaDB + archival"]
    end

    Phase1 --> HardwareOptimization
    Phase2 --> HardwareOptimization
    Phase3 --> HardwareOptimization

• Phase 1: A developer creates a "micropayments" submesh via YAML, sets low fees.
• Phase 2: Nodes vote to increase block size for this submesh during peak hours.
• Phase 3: Malicious nodes spamming the submesh are isolated via manual voting.

• Simpler Debugging: No black-box AI logic.
• Lower Resource Use: Eliminates GPU-heavy ML workloads.
• Transparency: Rules and thresholds are manually defined.

Developed by Blackbeard | Ten Titanics | GitHub

© 2023-2025 Blackbeard. All rights reserved.