HashHalo

HashHalo is a lightweight simulation of consistent hashing to demonstrate how distributed load balancing works across server nodes. The project simulates key distribution across a hash ring and visualizes the minimal reallocation that occurs when servers join or leave the system.

Project Objectives

• Implement consistent hashing from scratch.

• Simulate server nodes and dynamic joining/leaving.

• Efficiently assign and reassign "keys" (requests/users/files) to nodes.

• Measure impact on reallocation and performance.

Optional: Add UI or metrics to visualize hash ring and load distribution.

Key Concepts

• Consistent Hashing: A technique to distribute data across a cluster in a way that minimizes rebalancing when nodes join or leave.

• Virtual Nodes: Improve uniformity by assigning multiple positions in the hash ring to a single server.

• Hash Ring: A circular space (0 to 2³² or based on hash function output) where keys and nodes are mapped using a hash function.

Tech Stack

Backend (Core Logic):

• Golang (ideal for low-latency logic, concurrency)

Optional Add-ons: Redis or MongoDB – simulate distributed storage

• Vue.js/React – to visualize hash ring and server loads

• gRPC/REST – simulate service calls

Project Structure

HashHalo/
│
├── src/
│   ├── hash_ring.go     # Implements the hash ring logic
│   ├── server_node.go   # Represents a server
│   ├── main.go          # Simulation / entry point
│
├── test/
│   └── hash_test.go     # Unit tests for consistent hashing
│
├── data/
│   └── keys.json        # Sample input keys to distribute
│
├── README.md
└── visualization/       # (Optional) UI to visualize hash ring

Feature Description

• AddNode(nodeID) Add a server to the ring
• RemoveNode(nodeID) Remove a server from the ring
• GetNode(key) Get the server that owns the key
• Rebalance(keys) Show how few keys are remapped on node changes
• Virtual Nodes Support Add multiple points per server
• Metrics (Keys/server, reallocation) Show how well load is balanced

Example Flow

• Start with 3 servers: A, B, C
• Insert 1000 keys (simulate user sessions or file storage)
• Observe which server handles which key
• Add a new server D
• Show how only ~1/N of the keys are remapped (not all)
• Visualize changes in server load