GLIN Chain - Substrate Blockchain for Federated Learning

🌐 Overview

GLIN Chain is the blockchain infrastructure powering the GLIN federated learning marketplace. Built with Substrate, it provides trustless task management, provider staking, and reward distribution for decentralized AI training.

Key Features

• 🔒 Trustless Task Escrow: Secure bounty locking for ML training tasks
• 💰 Provider Staking: Economic security through stake-based participation
• 🎯 Batch Rewards: Efficient merkle-tree based reward distribution
• 🛡️ Slashing Mechanism: Automated penalties for malicious behavior
• 🔍 ZKP Validation: On-chain verification for high-value computations

🚀 Quick Start

Prerequisites

# Install Rust
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Install Substrate dependencies
sudo apt update && sudo apt install -y git clang curl libssl-dev llvm libudev-dev make protobuf-compiler

# Clone the repository
git clone https://github.com/glin-ai/glin-chain.git
cd glin-chain

Build & Run

# Build the node
cargo build --release

# Run development node
./target/release/glin-node --dev

# Run with custom chain spec
./target/release/glin-node --chain=local

Docker

# Build Docker image
docker build -t glin-chain .

# Run container
docker run -p 9944:9944 -p 9933:9933 glin-chain

🏗️ Architecture

Pallets

Pallet	Purpose	Key Functions
task-registry	Task lifecycle management	create_task, cancel_task, complete_task
provider-staking	Provider registration & staking	register_provider, slash_provider, withdraw_stake
reward-distribution	Batch reward processing	create_batch, submit_rewards, settle_batch
validation-zkp	Zero-knowledge proof verification	submit_proof, verify_gradient
reputation	Provider reputation tracking	update_score, get_reputation

Economic Model

• Token: GLIN
• Total Supply: 1,000,000,000 GLIN
• Minimum Provider Stake: 1,000 GLIN
• Minimum Task Bounty: 10 GLIN
• Platform Fee: 2% of rewards
• Slashing Rate: 10% for violations

🔧 Configuration

Chain Specification

# Generate chain spec
./target/release/glin-node build-spec --chain=local > customSpec.json

# Generate raw chain spec
./target/release/glin-node build-spec --chain=customSpec.json --raw > customSpecRaw.json

Network Ports

• P2P: 30333
• RPC: 9933
• WebSocket: 9944
• Prometheus: 9615

🧪 Testing

# Run all tests
cargo test

# Run pallet tests
cargo test -p pallet-task-registry
cargo test -p pallet-provider-staking
cargo test -p pallet-reward-distribution

# Run integration tests
cargo test --test '*'

# Run benchmarks
cargo test --features runtime-benchmarks

🔗 Integration

JavaScript/TypeScript

import { ApiPromise, WsProvider } from '@polkadot/api';

const provider = new WsProvider('ws://localhost:9944');
const api = await ApiPromise.create({ provider });

// Create a task
const tx = api.tx.taskRegistry.createTask(
  'Image Classification',
  'ResNet',
  1000000000000, // 1 GLIN bounty
  3, // min providers
  10, // max providers
  'QmHash...', // IPFS hash
  { minVramGb: 8, minComputeCapability: 75, minBandwidthMbps: 100 }
);

await tx.signAndSend(alice);

Python

from substrateinterface import SubstrateInterface

substrate = SubstrateInterface(
    url="ws://localhost:9944",
    type_registry_preset='substrate-node'
)

# Query provider info
result = substrate.query(
    module='ProviderStaking',
    storage_function='Providers',
    params=['5GrwvaEF5zXb26Fz9rcQpDWS57CtERHpNehXCPcNoHGKutQY']
)

📊 Monitoring

Prometheus Metrics

# prometheus.yml
scrape_configs:
  - job_name: 'glin-node'
    static_configs:
      - targets: ['localhost:9615']

Grafana Dashboard

Import our Grafana dashboard for real-time metrics.

🛠️ Development

Adding a New Pallet

# Generate pallet template
substrate-node-new-pallet my-pallet

# Add to runtime
# Edit runtime/src/lib.rs

Upgrading Runtime

# Build new runtime
cargo build --release -p glin-runtime

# Submit upgrade transaction
# Via polkadot.js or CLI

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Setup

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Code Style

# Format code
cargo fmt

# Run clippy
cargo clippy -- -D warnings

📚 Documentation

• Pallet Documentation
• RPC Documentation
• Chain Specification
• Integration Guide

🔐 Security

Audits

• Pallet logic audit (Planned Q1 2025)
• Runtime audit (Planned Q2 2025)

Bug Bounty

Report security vulnerabilities to [email protected]. See SECURITY.md for our bug bounty program.

📜 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🔗 Links

• Website: https://glin.ai
• Documentation: https://docs.glin.ai
• Discord: Join our community
• Twitter: @glin_ai

🙏 Acknowledgments

Built with Substrate by Parity Technologies

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Made with ❤️ by the GLIN AI team