ADSA-DHT-P2P: Distributed Hash Table & P2P Simulator

Welcome to the ADSA-DHT-P2P project! This is a high-performance simulation of a Distributed Hash Table (DHT) using Consistent Hashing, designed as a foundation for a Peer-to-Peer (P2P) file-sharing network.

It visualizes how data is distributed across a dynamic set of nodes, demonstrating how nodes can join or leave the network with minimal data redistribution.

---

Core Features

• Consistent Hashing: Implements a robust DHT where nodes and data keys are mapped to a 160-bit circular identifier space (SHA-1).
• Dynamic Node Management: Add or remove nodes on the fly. The system automatically redistributes only the necessary keys to maintain balance.
• P2P File Layer: A conceptual layer that manages "files" as keys and "peers" as values, allowing multiple peers to share the same file.
• Visual Simulator: A real-time SVG-based visualization tool (currently being modularized!) to see the "Ring" in action.
• FastAPI Integration: (Coming Soon/In Progress) Leveraging modern Python for a high-performance, asynchronous API.

---

Data Structures & Architecture

1. Consistent Hashing Logic

The network is modeled as a circular "ring" from $0$ to $2^{160}-1$.

• Identifying Nodes: Each node's name is hashed to determine its position on the ring.
• Identifying Data: Each file name is hashed to determine its position.
• Lookup Rule: A key is stored on the first node encountered when moving clockwise from the key's position on the ring.

2. Primary Classes

ConsistentHashDHT

The "brain" of the system.

• nodes: A hash map (dict) where key is the ring position and value is the Node object.
• sorted_keys: A sorted list of all active node positions, allowing for $O(\log N)$ lookups using binary search (bisect).

Node (Peer)

Represents a physical or virtual machine in the network.

• name: Human-readable identifier.
• data: A local dictionary containing the subset of the global DHT that this node is responsible for.

P2PFileSharing

An abstraction layer for file operations.

• Uses the DHT to map file_name $\rightarrow$ [list_of_peer_names].

---

System Flow (Mermaid)

graph TD
    User[User/Client] -->|Upload File| P2P[P2P Layer]
    P2P -->|Hash Filename| DHT[Consistent Hash DHT]
    DHT -->|Binary Search| Ring[Hash Ring]
    Ring -->|Find Successor| Node[Target Node]
    Node -->|Store Mapping| Storage[(Local Data)]
    
    subgraph "Data Redistribution"
    NewNode[New Node Joins] -->|Calculate Hash| DHT
    DHT -->|Identify Range| Successor[Successor Node]
    Successor -->|Transfer Keys| NewNode
    end

Loading

---

🛠️ Tech Stack

• Backend: Python 3.10+, FastAPI
• Frontend: React (Vite), Framer Motion, Lucide Icons, Axios
• Algorithms: SHA-1 Consistent Hashing, Binary Search (Bisect)

---

🏃 Getting Started

1. Backend (FastAPI)

# Install dependencies
pip install -r requirements.txt

# Start the server
python main.py

The API will be available at http://127.0.0.1:8000. You can see the interactive docs at /docs.

2. Frontend (React)

cd frontend
npm install
npm run dev

Open the provided local URL (usually http://localhost:5173).

---

System Architecture

Modular Frontend

The UI is built with React for true modularity:

• App.jsx: Manages global network state and API polling.
• App.css: Implements a glassmorphic, premium dark theme.
• SVG Engine: A declarative SVG-based visualization using framer-motion for smooth node transitions.

---

Planned Improvements & Learning path

1. Virtual Nodes: Help balance the data distribution. To implement this, try hashing each node name multiple times (e.g., Node1-v1, Node1-v2) and mapping them all to the same physical node.
2. Replication: Store data on the next $k$ nodes to ensure fault tolerance.
3. Pydantic Validation: Explore main.py to see how Pydantic ensures data integrity.

---