Load Balancing and Consistent Hashing Project

By Brandon Mahdavi

This project implements and tests three load-balancing strategies in Python:

• Round Robin
• Weighted Round Robin
• Consistent Hashing (with virtual nodes / replicas)

Project Files

• load_balancer.py: Core LoadBalancer class and strategy routing logic.
• server.py: Server model with id, weight, and request counter.
• consistent_hash.py: Hash-ring implementation (add_node, remove_node, get_node).
• simulation.py: End-to-end simulation over 10,000 requests.
• analysis.md: Required analysis for resilience, stability, and replica distribution.
• tests/test_lb.py: Unit tests for all strategies and edge cases.

Requirements

• Python 3.12+ (Python 3.x works for this codebase)

How To Run

Run all unit tests:

python3 -m unittest discover tests

Run the simulation:

python3 simulation.py

Or use the Makefile shortcuts:

make test
make run

Current Verification Status

• Unit tests passing: 21/21
• Simulation scenarios completed:
  • Round Robin
  • Weighted Round Robin
  • Consistent Hashing
  • Replica comparison (1, 3, 50, 150 replicas)
  • Resilience test after server removal

Notes

• Consistent hashing distribution with only 3 replicas is intentionally uneven.
• Increasing replica count improves load balance significantly.

Background

Built for the load-balancing unit of SDSU's CS496 (cloud computing). The module and test stubs were provided by the course; the strategy implementations, hash ring, tests, simulation scenarios and analysis are mine.