Project Overview

This project consists of a high-performance server and client implementation in C++, along with extensive benchmarking using Python. The benchmarks generate various performance graphs, including box plots and pie charts.

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Project Structure

├── benchmark
│   ├── bench_box_plot.py      # Script to generate box plot from benchmark data
│   ├── benchmark_fast.py      # Fast execution benchmark
│   └── benchmark_slow.py      # Slow execution benchmark
├── benchmark_fast_results.png # Image of fast benchmark results
├── benchmark_slow_results.png # Image of slow benchmark results
├── docker-compose.yml         # Docker Compose configuration
├── Dockerfile                 # Dockerfile to containerize the project
├── extensive_benchmark_results.png # Image of extensive benchmark results
├── Makefile                   # Makefile for building the project
├── README.md                  # This README file
├── requirements.txt            # Python dependencies
├── response_time_boxplot.png   # Image of response time distribution (Box plot)
├── response_time_piechart.png  # Image of response time distribution (Pie chart)
├── src
│   ├── client.cc               # Client implementation
│   ├── command.cc, command.h   # Command processing logic
│   ├── conn.h                  # Connection handling
│   ├── epoll_manager.cc, epoll_manager.h # Epoll-based event management
│   ├── server.cc, server.h     # Server implementation
│   └── utils.h                 # Utility functions
└── test
    └── test.py                 # Python test script for validation

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Running the Project

1️⃣ Running with Docker

Build the Docker Image

docker build -t my_server .

Run the Server

docker run -p 6969:6969 --name server_container my_server

Run the Client

docker run --network host my_server ./client

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2️⃣ Running Benchmarks

Setup a Python Virtual Environment

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

Install Dependencies

pip install -r requirements.txt

Run Benchmark Scripts

python benchmark/benchmark_fast.py
python benchmark/benchmark_slow.py
python benchmark/bench_box_plot.py

Benchmark Results

For Fast Benchmark

Total Requests: 1000
Successful Requests: 1000
Total Time: 0.028688 sec
Average Time per Request: 0.000029 sec

For Slow Benchmark

Total Requests: 5000
Successful Requests: 5000
Total Time: 1.049078 sec
Average Time per Request: 0.000210 sec
Median Time per Request: 0.000118 sec
Max Time per Request: 0.010576 sec
Min Time per Request: 0.000015 sec

Generated Benchmark Results

Below are the benchmark images generated:

• Fast Benchmark:
• Slow Benchmark:
• Response Time Box Plot:

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3️⃣ Running Tests

Run the Python Test Suite

python test/test.py

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4️⃣ Running Locally (Without Docker)

Build the Project

make

Run the Server

./server

Run the Client

./client

Clean the Build

make clean

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Notes

• Ensure that the server is running before executing the client or benchmark scripts.
• The benchmarks will generate performance graphs to analyze the efficiency of the server.
• Docker is recommended for an isolated and reproducible environment.

🚀 Happy Coding!