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Aljaz Ceru
8b6fd8b89d
Advanced Lightning Network channel fee optimization system with: ✅ Intelligent inbound fee strategies (beyond charge-lnd) ✅ Automatic rollback protection for safety ✅ Machine learning optimization from historical data ✅ High-performance gRPC + REST API support ✅ Enterprise-grade security with method whitelisting ✅ Complete charge-lnd compatibility Features: - Policy-based fee management with advanced strategies - Balance-based and flow-based optimization algorithms - Revenue maximization focus vs simple rule-based approaches - Comprehensive security analysis and hardening - Professional repository structure with proper documentation - Full test coverage and example configurations Architecture: - Modern Python project structure with pyproject.toml - Secure gRPC integration with REST API fallback - Modular design: API clients, policy engine, strategies - SQLite database for experiment tracking - Shell script automation for common tasks Security: - Method whitelisting for LND operations - Runtime validation of all gRPC calls - No fund movement capabilities - fee management only - Comprehensive security audit completed - Production-ready with enterprise standards 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
140 lines
3.3 KiB
Plaintext
140 lines
3.3 KiB
Plaintext
# Advanced Policy Configuration - Showcasing improvements over charge-lnd
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# This configuration uses all the advanced features including machine learning
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[default]
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final = false
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base_fee_msat = 1000
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fee_ppm = 1000
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time_lock_delta = 80
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enable_auto_rollback = true
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rollback_threshold = 0.25
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learning_enabled = true
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[revenue-maximization]
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# High-value channels with learning enabled
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chan.min_capacity = 10000000
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activity.level = high, medium
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strategy = revenue_max
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learning_enabled = true
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enable_auto_rollback = true
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rollback_threshold = 0.2
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priority = 5
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[competitive-pricing]
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# Channels where we compete with many alternatives - use inbound discounts
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network.min_alternatives = 5
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peer.fee_ratio.min = 0.7
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peer.fee_ratio.max = 1.3
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strategy = inbound_discount
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fee_ppm = 1200
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inbound_fee_ppm = -75
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inbound_base_fee_msat = -300
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priority = 10
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[premium-peers]
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# Special rates for known high-value peers (replace with actual pubkeys)
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node.id = 033d8656219478701227199cbd6f670335c8d408a92ae88b962c49d4dc0e83e025, 03cde60a6323f7122d5178255766e38114b4722ede08f7c9e0c5df9b912cc201d6
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strategy = static
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fee_ppm = 750
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inbound_fee_ppm = -50
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inbound_base_fee_msat = -250
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enable_auto_rollback = false
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priority = 5
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[flow-based-optimization]
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# Channels with good flow patterns - optimize based on activity
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flow.7d.min = 5000000
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strategy = flow_based
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learning_enabled = true
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enable_auto_rollback = true
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rollback_threshold = 0.3
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priority = 15
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[balance-extreme-drain]
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# Very unbalanced channels (>90% local) - aggressive rebalancing
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chan.min_ratio = 0.9
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strategy = balance_based
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fee_ppm = 100
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inbound_fee_ppm = -200
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inbound_base_fee_msat = -1000
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max_fee_ppm = 300
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priority = 8
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[balance-extreme-preserve]
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# Very low balance channels (<10% local) - aggressive preservation
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chan.max_ratio = 0.1
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strategy = balance_based
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fee_ppm = 3000
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inbound_fee_ppm = 100
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inbound_base_fee_msat = 500
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min_fee_ppm = 2000
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priority = 8
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[small-channel-activation]
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# Small channels that are inactive - make them competitive
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chan.max_capacity = 1000000
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activity.level = inactive, low
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strategy = static
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fee_ppm = 150
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inbound_fee_ppm = -100
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max_fee_ppm = 400
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priority = 25
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[large-inactive-penalty]
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# Large but inactive channels - higher fees to encourage closure or activation
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chan.min_capacity = 5000000
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activity.level = inactive
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strategy = static
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fee_ppm = 2500
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inbound_fee_ppm = 50
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min_fee_ppm = 2000
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priority = 20
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[medium-flow-optimization]
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# Medium activity channels - gradual optimization
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activity.level = medium
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flow.7d.min = 1000000
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flow.7d.max = 10000000
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strategy = proportional
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fee_ppm = 1200
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inbound_fee_ppm = -25
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learning_enabled = true
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priority = 30
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[old-channels]
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# Channels older than 90 days - conservative management
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chan.min_age_days = 90
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strategy = static
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fee_ppm = 800
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inbound_fee_ppm = -10
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enable_auto_rollback = false
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priority = 35
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[new-channels]
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# Channels younger than 7 days - give time to establish flow
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chan.max_age_days = 7
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strategy = static
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fee_ppm = 500
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inbound_fee_ppm = -50
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max_fee_ppm = 1000
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priority = 12
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[discourage-routing]
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# Channels we want to discourage (e.g., poorly connected peers)
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chan.max_ratio = 0.05
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chan.min_capacity = 1000000
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strategy = static
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fee_ppm = 5000
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inbound_fee_ppm = 200
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min_fee_ppm = 4000
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priority = 90
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[catch-all]
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# Final policy with learning enabled
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strategy = revenue_max
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fee_ppm = 1000
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inbound_fee_ppm = 0
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learning_enabled = true
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enable_auto_rollback = true
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rollback_threshold = 0.3
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priority = 100 |