Implementation details for Random Walk Module for Continuous Peer Discovery in py-libp2p

[seetadev]

Implementation

We propose implementing a Random Walk module for the DHT in py-libp2p.

Goals:

• Maintain a healthy, up-to-date routing table by periodically discovering new peers.
• Improve query success rates and reduce lookup latency in dynamic, churn-heavy networks.
• Bring py-libp2p closer to feature parity with Go-libp2p and JS-libp2p, improving cross-implementation interoperability.

Key Features:

1. Random Walk Scheduler

   • Runs as a background coroutine.
   • Periodically initiates random FIND_NODE queries using randomly generated peer IDs.

2. Configurable Parameters

   • Walk interval: Time between successive walks.
   • Concurrency: Number of simultaneous walks.
   • Timeouts: Max time per lookup.

3. Integration with Existing DHT Client

   • Uses the current Kademlia DHT implementation.
   • Updates the routing table with discovered peers.

4. Start/Stop Controls

   • Expose simple APIs to start or stop the Random Walk process (useful for testing or selective use cases).

5. Logging & Metrics

   • Add optional logging for debugging (e.g., peers discovered per walk).
   • Expose hooks for monitoring modules to collect discovery metrics.

Milestones

• Random Walk module implemented as a separate class/module (random_walk.py or integrated into DHT).
• Configurable options for walk interval, concurrency, and lookup timeouts.
• APIs to start/stop the Random Walk process at runtime.
• Integration tests to validate that the module updates the routing table with new peers.
• Unit tests to verify correct scheduling, error handling, and concurrency behavior.
• Documentation for usage, configuration, and developer guidelines.
• Performance validation: Ensure the module does not significantly degrade node performance (e.g., excessive resource use).