DAA Prime Coordinator

Governance and coordination layer for the Prime distributed machine learning framework. Provides decentralized coordination, task distribution, consensus mechanisms, and economic incentives through deep integration with the DAA ecosystem.

Overview

DAA Prime Coordinator serves as the governance and orchestration layer for distributed ML training, providing:

• Decentralized Coordination: Consensus-based task distribution without central authority
• Economic Incentives: Token-based rewards for quality contributions via DAA Economy
• Governance Integration: Rule-based policies through DAA Rules system
• Fault Tolerance: Byzantine fault-tolerant coordination protocols
• Performance Monitoring: Real-time training metrics and node reliability scoring

Features

• 🎯 Smart Coordination: Intelligent task assignment based on node capabilities
• 💰 Economic Incentives: Automated reward distribution for quality work
• 🏛️ Governance: Decentralized decision making with stakeholder voting
• 🛡️ Byzantine Fault Tolerance: Robust against malicious and faulty nodes
• 📊 Analytics: Comprehensive training progress and node performance tracking
• 🔄 Self-Healing: Automatic recovery from coordinator failures

Installation

Add this to your Cargo.toml:

[dependencies]
daa-prime-coordinator = "0.2.1"
daa-prime-core = "0.2.1"
daa-ai = "0.2.1"
daa-rules = "0.2.1"
tokio = { version = "1.0", features = ["full"] }

Quick Start

Basic Coordinator

use daa_prime_coordinator::{CoordinatorNode, CoordinatorConfig};
use anyhow::Result;

#[tokio::main]
async fn main() -> Result<()> {
    // Create coordinator with default configuration
    let config = CoordinatorConfig::default();
    let coordinator = CoordinatorNode::new("coordinator-001".to_string(), config).await?;
    
    // Start coordination services
    coordinator.start().await?;
    
    Ok(())
}

Custom Configuration

use daa_prime_coordinator::{CoordinatorNode, CoordinatorConfig};
use std::time::Duration;

let config = CoordinatorConfig {
    min_nodes_for_round: 5,           // Minimum participants per round
    heartbeat_timeout_ms: 10000,      // 10 second heartbeat timeout
    task_timeout_ms: 300000,          // 5 minute task timeout
    consensus_threshold: 0.75,        // 75% consensus required
};

let coordinator = CoordinatorNode::new("coordinator-001".to_string(), config).await?;

Node Management

use daa_prime_coordinator::{CoordinatorNode, NodeInfo};

let coordinator = CoordinatorNode::new("coordinator-001".to_string(), config).await?;

// Add a trainer node
let node_info = NodeInfo {
    node_id: "trainer-001".to_string(),
    node_type: "trainer".to_string(),
    last_heartbeat: current_timestamp(),
    reliability_score: 0.95,
};

coordinator.add_node(node_info).await?;

// Get coordinator status
let status = coordinator.get_status().await?;
println!("Active nodes: {}, Pending tasks: {}", 
    status.active_nodes, status.pending_tasks);

Core Concepts

Training Round Coordination

use daa_prime_coordinator::{TrainingRound, RoundConfig};

// Configure training round
let round_config = RoundConfig {
    round_id: 42,
    min_participants: 5,
    max_participants: 20,
    deadline: Duration::from_secs(600), // 10 minutes
    model_version: 15,
    aggregation_strategy: AggregationStrategy::FederatedAveraging,
};

// Start new training round
coordinator.start_training_round(round_config).await?;

// Monitor round progress
let progress = coordinator.get_round_progress(42).await?;
println!("Round 42: {}/{} participants completed", 
    progress.completed, progress.total);

Task Distribution

use daa_prime_coordinator::{TrainingTask, TaskPriority};

// Create training task
let task = TrainingTask {
    task_id: "gradient_computation_1".to_string(),
    task_type: "gradient_computation".to_string(),
    deadline: current_timestamp() + 300, // 5 minutes from now
    reward_amount: 100, // Token reward
    priority: TaskPriority::High,
    required_capabilities: vec!["gpu".to_string(), "pytorch".to_string()],
};

// Distribute task to eligible nodes
coordinator.distribute_task(task).await?;

Consensus Protocol

use daa_prime_coordinator::{ConsensusManager, ConsensusConfig};

let consensus_config = ConsensusConfig {
    algorithm: ConsensusAlgorithm::PBFT, // Practical Byzantine Fault Tolerance
    byzantine_tolerance: 0.33,           // Tolerate up to 1/3 byzantine nodes
    timeout: Duration::from_secs(30),
    max_rounds: 10,
};

let consensus = ConsensusManager::new(consensus_config);

// Propose a value for consensus
let proposal = ConsensusProposal {
    round: 1,
    value: serde_json::to_vec(&aggregated_gradients)?,
    proposer: coordinator.node_id(),
};

consensus.propose(proposal).await?;

Advanced Usage

Economic Incentives Integration

use daa_prime_coordinator::{CoordinatorNode, EconomicConfig};
use daa_economy::{TokenManager, RewardCalculator};

// Configure economic incentives
let economic_config = EconomicConfig {
    base_reward: 100,              // Base tokens per task
    quality_multiplier: 2.0,       // Bonus for high-quality work
    reliability_bonus: 1.5,        // Bonus for reliable nodes
    slashing_rate: 0.1,           // Penalty for bad behavior
};

let coordinator = CoordinatorNode::with_economic_config(
    "coordinator-001".to_string(),
    config,
    economic_config
).await?;

// Automatic reward distribution after task completion
coordinator.enable_automatic_rewards().await?;

Governance Integration

use daa_prime_coordinator::{GovernanceManager, ProposalType};
use daa_rules::{Rule, PolicyEngine};

// Create governance proposal
let proposal = GovernanceProposal {
    proposal_id: "increase_min_nodes".to_string(),
    proposal_type: ProposalType::ParameterChange,
    description: "Increase minimum nodes per round to 10".to_string(),
    changes: vec![
        ParameterChange {
            key: "min_nodes_for_round".to_string(),
            old_value: "5".to_string(),
            new_value: "10".to_string(),
        }
    ],
    voting_deadline: current_timestamp() + 86400, // 24 hours
};

// Submit for stakeholder voting
governance.submit_proposal(proposal).await?;

// Vote on proposal (as a stakeholder)
governance.vote("increase_min_nodes", VoteChoice::Approve, 1000).await?; // 1000 token weight

Custom Node Selection

use daa_prime_coordinator::{NodeSelector, SelectionCriteria};

// Implement custom node selection strategy
struct PerformanceBasedSelector;

impl NodeSelector for PerformanceBasedSelector {
    async fn select_nodes(
        &self,
        available_nodes: &[NodeInfo],
        criteria: &SelectionCriteria,
    ) -> Result<Vec<NodeInfo>> {
        let mut nodes = available_nodes.to_vec();
        
        // Sort by reliability score and recent performance
        nodes.sort_by(|a, b| {
            let score_a = a.reliability_score * a.recent_performance_score;
            let score_b = b.reliability_score * b.recent_performance_score;
            score_b.partial_cmp(&score_a).unwrap()
        });
        
        // Select top N nodes
        Ok(nodes.into_iter().take(criteria.max_nodes).collect())
    }
}

// Use custom selector
coordinator.set_node_selector(Box::new(PerformanceBasedSelector)).await?;

Multi-Coordinator Setup

use daa_prime_coordinator::{CoordinatorCluster, ClusterConfig};

// Set up coordinator cluster for high availability
let cluster_config = ClusterConfig {
    cluster_id: "main_cluster".to_string(),
    coordinators: vec![
        "coordinator-001".to_string(),
        "coordinator-002".to_string(),
        "coordinator-003".to_string(),
    ],
    leader_election: LeaderElection::Raft,
    failover_timeout: Duration::from_secs(30),
};

let cluster = CoordinatorCluster::new(cluster_config).await?;

// Coordinators automatically handle:
// - Leader election
// - Load balancing
// - Failover
// - State synchronization

Performance Monitoring

use daa_prime_coordinator::{MetricsCollector, PerformanceMetrics};

// Set up comprehensive monitoring
let metrics = MetricsCollector::new();
coordinator.set_metrics_collector(metrics).await?;

// Real-time monitoring loop
loop {
    let performance = coordinator.get_performance_metrics().await?;
    
    println!("Coordinator Performance:");
    println!("  Active rounds: {}", performance.active_rounds);
    println!("  Tasks/second: {:.2}", performance.task_throughput);
    println!("  Average task completion: {:.1}s", performance.avg_task_completion);
    println!("  Node reliability: {:.1}%", performance.avg_node_reliability * 100.0);
    
    // Alert on performance degradation
    if performance.task_throughput < 1.0 {
        eprintln!("WARNING: Low task throughput detected!");
    }
    
    tokio::time::sleep(Duration::from_secs(30)).await;
}

Configuration

Coordinator Configuration

use daa_prime_coordinator::CoordinatorConfig;
use std::time::Duration;

let config = CoordinatorConfig {
    // Basic coordination parameters
    min_nodes_for_round: 3,
    max_nodes_per_round: 100,
    heartbeat_timeout_ms: 5000,
    task_timeout_ms: 60000,
    
    // Consensus parameters
    consensus_threshold: 0.66,      // 2/3 majority
    byzantine_tolerance: 0.33,      // Tolerate 1/3 byzantine nodes
    max_consensus_rounds: 5,
    
    // Economic parameters
    enable_rewards: true,
    base_reward_amount: 100,
    quality_threshold: 0.8,
    
    // Performance parameters
    max_concurrent_rounds: 10,
    task_queue_size: 1000,
    node_cache_ttl: Duration::from_secs(300),
};

Security Configuration

use daa_prime_coordinator::SecurityConfig;

let security_config = SecurityConfig {
    // Authentication
    require_node_signatures: true,
    verify_task_results: true,
    
    // Anti-sybil measures
    min_stake_requirement: 1000,    // Minimum tokens to participate
    reputation_threshold: 0.7,      // Minimum reputation score
    
    // Rate limiting
    max_tasks_per_node_per_hour: 100,
    max_heartbeats_per_minute: 2,
    
    // Byzantine fault tolerance
    enable_bft_consensus: true,
    slashing_enabled: true,
    evidence_preservation_period: Duration::from_secs(86400 * 7), // 1 week
};

Testing

Unit Tests

#[cfg(test)]
mod tests {
    use super::*;
    use daa_prime_coordinator::test_utils::*;
    
    #[tokio::test]
    async fn test_coordinator_creation() {
        let config = CoordinatorConfig::default();
        let coordinator = CoordinatorNode::new("test-coord".to_string(), config).await.unwrap();
        
        let status = coordinator.get_status().await.unwrap();
        assert_eq!(status.active_nodes, 0);
        assert_eq!(status.current_round, 0);
    }
    
    #[tokio::test]
    async fn test_node_management() {
        let coordinator = create_test_coordinator().await;
        
        let node_info = NodeInfo {
            node_id: "test-node".to_string(),
            node_type: "trainer".to_string(),
            last_heartbeat: current_timestamp(),
            reliability_score: 0.9,
        };
        
        coordinator.add_node(node_info.clone()).await.unwrap();
        
        let status = coordinator.get_status().await.unwrap();
        assert_eq!(status.active_nodes, 1);
        
        let nodes = coordinator.list_nodes().await.unwrap();
        assert_eq!(nodes[0].node_id, "test-node");
    }
}

Integration Tests

#[cfg(test)]
mod integration_tests {
    use super::*;
    use daa_prime_trainer::TrainerNode;
    
    #[tokio::test]
    async fn test_full_training_round() {
        // Set up coordinator
        let coordinator = CoordinatorNode::new(
            "test-coordinator".to_string(),
            CoordinatorConfig::default()
        ).await.unwrap();
        
        // Set up multiple trainers
        let mut trainers = Vec::new();
        for i in 0..5 {
            let trainer = TrainerNode::new(format!("trainer-{}", i)).await.unwrap();
            trainers.push(trainer);
        }
        
        // Register trainers with coordinator
        for trainer in &trainers {
            let node_info = NodeInfo {
                node_id: trainer.node_id().clone(),
                node_type: "trainer".to_string(),
                last_heartbeat: current_timestamp(),
                reliability_score: 0.95,
            };
            coordinator.add_node(node_info).await.unwrap();
        }
        
        // Start training round
        let round_config = RoundConfig::default();
        coordinator.start_training_round(round_config).await.unwrap();
        
        // Wait for round completion
        tokio::time::sleep(Duration::from_secs(10)).await;
        
        // Verify round completed successfully
        let status = coordinator.get_status().await.unwrap();
        assert!(status.completed_rounds > 0);
    }
}

Load Testing

#[cfg(test)]
mod load_tests {
    use super::*;
    use std::sync::Arc;
    use tokio::sync::Semaphore;
    
    #[tokio::test]
    async fn test_high_load_coordination() {
        let coordinator = create_test_coordinator().await;
        
        // Simulate 1000 concurrent node registrations
        let semaphore = Arc::new(Semaphore::new(100)); // Limit to 100 concurrent
        let mut handles = Vec::new();
        
        for i in 0..1000 {
            let coordinator = coordinator.clone();
            let semaphore = semaphore.clone();
            
            let handle = tokio::spawn(async move {
                let _permit = semaphore.acquire().await.unwrap();
                
                let node_info = NodeInfo {
                    node_id: format!("load-test-node-{}", i),
                    node_type: "trainer".to_string(),
                    last_heartbeat: current_timestamp(),
                    reliability_score: 0.9,
                };
                
                coordinator.add_node(node_info).await.unwrap();
            });
            
            handles.push(handle);
        }
        
        // Wait for all registrations to complete
        for handle in handles {
            handle.await.unwrap();
        }
        
        let status = coordinator.get_status().await.unwrap();
        assert_eq!(status.active_nodes, 1000);
    }
}

Deployment

Single Coordinator

# Start coordinator
cargo run --bin prime-coordinator -- \
    --node-id coordinator-001 \
    --config config.json \
    --port 8080 \
    --enable-governance \
    --enable-economics

Coordinator Cluster

# Start first coordinator (will become leader)
cargo run --bin prime-coordinator -- \
    --node-id coordinator-001 \
    --cluster-config cluster.json \
    --bootstrap

# Start additional coordinators
cargo run --bin prime-coordinator -- \
    --node-id coordinator-002 \
    --cluster-config cluster.json \
    --join coordinator-001:8080

cargo run --bin prime-coordinator -- \
    --node-id coordinator-003 \
    --cluster-config cluster.json \
    --join coordinator-001:8080

Docker Deployment

FROM rust:1.70 as builder

WORKDIR /app
COPY . .
RUN cargo build --release --bin prime-coordinator

FROM debian:bookworm-slim
RUN apt-get update && apt-get install -y ca-certificates && rm -rf /var/lib/apt/lists/*
COPY --from=builder /app/target/release/prime-coordinator /usr/local/bin/

EXPOSE 8080
CMD ["prime-coordinator", "--config", "/etc/coordinator/config.json"]

# docker-compose.yml
version: '3.8'
services:
  coordinator-1:
    image: daa-prime-coordinator:latest
    ports:
      - "8080:8080"
    environment:
      - NODE_ID=coordinator-001
      - CLUSTER_MODE=true
    volumes:
      - ./config:/etc/coordinator
    
  coordinator-2:
    image: daa-prime-coordinator:latest
    ports:
      - "8081:8080"
    environment:
      - NODE_ID=coordinator-002
      - CLUSTER_MODE=true
      - BOOTSTRAP_PEER=coordinator-1:8080
    volumes:
      - ./config:/etc/coordinator

Monitoring and Observability

Prometheus Metrics

use daa_prime_coordinator::metrics::PrometheusExporter;

// Export metrics for Prometheus
let exporter = PrometheusExporter::new();
coordinator.set_metrics_exporter(exporter).await?;

// Metrics exported:
// - daa_coordinator_active_nodes
// - daa_coordinator_active_rounds  
// - daa_coordinator_task_completion_time
// - daa_coordinator_consensus_duration
// - daa_coordinator_byzantine_faults_detected

Grafana Dashboard

{
  "dashboard": {
    "title": "DAA Prime Coordinator",
    "panels": [
      {
        "title": "Active Nodes",
        "type": "stat",
        "targets": [
          {
            "expr": "daa_coordinator_active_nodes"
          }
        ]
      },
      {
        "title": "Task Throughput",
        "type": "graph", 
        "targets": [
          {
            "expr": "rate(daa_coordinator_tasks_completed_total[5m])"
          }
        ]
      }
    ]
  }
}

Troubleshooting

Common Issues

1. Consensus Timeouts

   // Increase consensus timeout for slow networks
   let config = CoordinatorConfig {
       consensus_timeout: Duration::from_secs(60),
       max_consensus_rounds: 10,
       ..Default::default()
   };
   

2. Byzantine Behavior Detection

   // Enable enhanced byzantine detection
   coordinator.enable_byzantine_detection(ByzantineDetectionConfig {
       gradient_similarity_threshold: 0.8,
       performance_deviation_threshold: 2.0,
       voting_pattern_analysis: true,
   }).await?;
   

3. High Memory Usage

   // Configure memory limits
   coordinator.set_memory_limits(MemoryLimits {
       max_cached_rounds: 100,
       max_node_history: 1000,
       cleanup_interval: Duration::from_secs(3600),
   }).await?;
   

Roadmap

• Advanced consensus algorithms (HotStuff, Tendermint)
• Cross-chain governance integration
• ML model governance and versioning
• Automated economic parameter tuning
• Advanced byzantine fault detection
• Integration with external monitoring systems

Contributing

Contributions are welcome! Please see our Contributing Guide for details.

License

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

Related Crates

• daa-prime-core: Core types and protocol definitions
• daa-prime-trainer: Training node implementation
• daa-prime-dht: Distributed hash table for coordination
• daa-prime-cli: Command-line interface

References

• Practical Byzantine Fault Tolerance - Castro & Liskov
• Federated Learning Systems - Bonawitz et al.
• Blockchain Governance - Miscione et al.

Support

• 📖 Documentation
• 🐛 Issue Tracker
• 💬 Discussions