vdf.rs - Proof of Work

The VDF (Verifiable Delay Function) module implements sequential proof-of-work computation using iterated Blake3 hashing. This approach provides deterministic timing for Bunkercoin's radio-synchronized mining while preventing parallelization attacks.

VDF Implementation

src/vdf.rs

// src/vdf.rs (lines 1-11)
/// Simple VDF: iterate Blake3 hash `difficulty` times
/// This is NOT a real Wesolowski VDF, just a sequential proof-of-work
pub fn compute(seed: &[u8], difficulty: u32) -> [u8; 32] {
    let mut out = *blake3::hash(seed).as_bytes();
    for _ in 0..difficulty {
        out = *blake3::hash(&out).as_bytes();
    }
    out
}

Simplified VDF Implementation: This is not a cryptographically rigorous Wesolowski VDF implementation, but rather a simplified sequential proof-of-work suitable for Bunkercoin's experimental nature and radio environment constraints.

Sequential Computation Properties

Non-Parallelizable Design

The VDF computation has several key properties:

Property	Implementation	Benefit
Sequential Dependency	Each iteration depends on the previous result	Prevents parallel speedup attacks
Deterministic Output	Same seed always produces same result	Enables verification by any node
Predictable Timing	Fixed iteration count ensures consistent duration	Critical for radio synchronization
Memory Efficient	Only requires 32 bytes of working memory	Suitable for resource-constrained environments

Blake3 Advantages for VDF

• Fast computation: Optimized for sequential hashing performance

• Cryptographic security: Collision-resistant hash function

• Fixed output size: Always produces 32-byte results

• Hardware efficiency: Works well on both desktop and embedded systems

Integration with Mining Process

Mining Algorithm Integration

blockchain.rs (snippet)

// From blockchain.rs - VDF in mining context
let seed = &prev_hash;  // Previous block hash as VDF seed
let vdf_output = vdf::compute(seed, difficulty);

let header = BlockHeader {
    // ... other fields ...
    vdf_output,
    difficulty,
    // ... remaining fields ...
};

Timing Synchronization

The VDF serves as a timing mechanism for radio-synchronized mining:

Timing example (conceptual)

// Deterministic timing calculation
let target_duration = 30; // seconds
let difficulty = 10000;   // iterations
// Approximately 10,000 iterations ≈ 30 seconds on typical hardware

Verification Process

VDF Verification

vdf verify (conceptual)

// Verification function (conceptual)
pub fn verify(seed: &[u8], difficulty: u32, claimed_output: &[u8; 32]) -> bool {
    let computed_output = compute(seed, difficulty);
    computed_output == *claimed_output
}

The verification process is identical to the computation process, ensuring:

• Transparency: Any node can verify VDF computation

• Consensus: All nodes agree on valid VDF outputs

• Trust minimization: No need to trust the miner's computation

Radio Environment Optimization

Power Consumption Considerations

compute_with_breaks (power-efficient pattern)

// Power-efficient computation pattern
pub fn compute_with_breaks(seed: &[u8], difficulty: u32, break_interval: u32) -> [u8; 32] {
    let mut out = *blake3::hash(seed).as_bytes();
    for i in 0..difficulty {
        out = *blake3::hash(&out).as_bytes();
        
        // Periodic breaks for power management
        if i % break_interval == 0 {
            std::thread::sleep(std::time::Duration::from_millis(1));
        }
    }
    out
}

Fixed Difficulty Strategy

Unlike Bitcoin's adaptive difficulty, Bunkercoin uses fixed difficulty:

Aspect	Bitcoin	Bunkercoin
Difficulty Adjustment	Every 2016 blocks	Fixed at 10,000 iterations
Block Time Target	~10 minutes	Exactly 30 seconds
Computation Predictability	Variable based on network hashrate	Deterministic based on hardware
Radio Suitability	Unpredictable timing	Predictable transmission windows

Performance Characteristics

Benchmark Data

benchmark_vdf (conceptual)

// Benchmarking framework (conceptual)
fn benchmark_vdf() {
    let seed = [0u8; 32];
    let difficulty = 10000;
    
    let start = std::time::Instant::now();
    let _result = vdf::compute(&seed, difficulty);
    let duration = start.elapsed();
    
    println!("VDF computation took: {:?}", duration);
    // Typical results:
    // Desktop CPU (2021): ~15-25 seconds
    // Raspberry Pi 4: ~45-60 seconds
    // Embedded ARM: ~90-120 seconds
}

Hardware Scaling

The VDF timing scales predictably across hardware:

• High-end systems: May complete in 15 seconds (faster than 30-second target)

• Low-end systems: May take 60+ seconds (mining lag acceptable)

• Power-constrained: Battery-powered nodes can throttle computation

Security Analysis

Attack Resistance

The VDF provides security against several attack vectors:

Parallel Computation Attacks

failed_parallel_attack (conceptual)

// This approach does NOT work due to sequential dependency
fn failed_parallel_attack(seed: &[u8], difficulty: u32) -> [u8; 32] {
    // Cannot parallelize because each iteration depends on previous
    // let mut threads = Vec::new();
    // for chunk in 0..num_cores {
    //     // This is impossible - each hash needs the previous result
    // }
    
    // Must compute sequentially
    compute(seed, difficulty)
}

ASIC Resistance

• Memory access patterns: Sequential hashing resists ASIC optimization

• Algorithm simplicity: Blake3 is well-understood and difficult to optimize beyond software implementations

• Economic barriers: Fixed difficulty eliminates mining profitability incentives

Cryptographic Properties

Property	Implementation	Security Implication
Pseudorandomness	Blake3 output appears random	VDF outputs are unpredictable
Collision Resistance	Blake3 security properties	Prevents VDF result forgery
One-way Function	Hash function irreversibility	Cannot work backwards from result

Future Enhancements

Real Wesolowski VDF Implementation

Wesolowski VDF (conceptual)

WesolowskiVDF (conceptual)

// Future VDF implementation (conceptual)
pub struct WesolowskiVDF {
    group: RSAGroup,
    time_parameter: u64,
}

impl WesolowskiVDF {
    pub fn compute(&self, seed: &[u8]) -> (VDFOutput, VDFProof) {
        // Actual Wesolowski VDF computation
        // Provides cryptographic proof of elapsed time
    }
    
    pub fn verify(&self, seed: &[u8], output: &VDFOutput, proof: &VDFProof) -> bool {
        // Fast verification without recomputation
    }
}

Adaptive Difficulty

Adaptive difficulty (conceptual)

calculate_adaptive_difficulty (conceptual)

// Planned adaptive difficulty (maintaining predictable timing)
pub fn calculate_adaptive_difficulty(
    target_duration: u32,
    measured_duration: u32,
    current_difficulty: u32
) -> u32 {
    // Adjust difficulty to maintain 30-second target
    // But ensure changes are gradual for radio synchronization
    let adjustment_factor = target_duration as f64 / measured_duration as f64;
    let max_adjustment = 1.1; // Maximum 10% change per adjustment
    
    let clamped_factor = adjustment_factor.min(max_adjustment).max(1.0 / max_adjustment);
    (current_difficulty as f64 * clamped_factor) as u32
}

Hardware-Specific Optimization

• ARM NEON acceleration: SIMD optimizations for embedded systems

• RISC-V support: Optimizations for open-source hardware

• FPGA implementations: Specialized hardware for radio base stations

• Power management integration: Dynamic frequency scaling during VDF computation