distributed-project

An implementation of a Chord - Distributed Hash Table (DHT) based app, for Distributed Systems course (NTUA)

Setup on Ubuntu Machine

git clone https://github.com/ntua-el20069/distributed-project.git

# if you intend to run the services on a remote cluster with nodes in the same network, 
# ensure you have team_12_ips.csv on the current working directory of the remote machine
# (copy the file from your local machine using scp command)

mv team_12_ips.csv distributed-project/ && cd distributed-project/

# python3.10 installation
sudo apt update && sudo apt upgrade
sudo add-apt-repository ppa:deadsnakes/ppa -y
sudo apt update
sudo apt install python3.10

sudo apt install python3.10-venv

# Creation of vitrual environment and installation of required python packages
python3.10 -m venv .venv
source .venv/bin/activate
python3.10 -m pip install -r requirements.txt

Run the app

Ensure you firstly open the bootstrap api, which is the node responsible for the other node joins into the P2P network. After you run the api for all nodes, your ready to insert key-value pairs into the DHT or query, by using the command line interface or the experiments script

• On local machine (set AWS = False in helpers.py), you can run python api.py [PORT_NUMBER] providing as ports 5000 (bootstrap node), 5001, 5002, ..., 5009
• On remote machines cluster (set AWS = True in helpers.py), you can run the api on ports 5000, 5001 for each of the 5 vms provided

Chordify client

Command line interface is provided based on python typer library Some of the available actions involve insertions of key-value pairs, queries based on keys, graceful departure of a node.

• Help for all available commands

python cli.py --help

• Help for a specific command (e.g. insert)

python cli.py insert --help

• Execute a specific command

python cli.py insert --key "hello" --value "world"

Experiments Script

You can run 3 types of experiments insert, query, requests by running the script following with the corresponding argument, as shown below for insert experiment.

python script.py insert

Experiments results

We ran experiments for strong and eventual consistency types and replication factor 1, 3, 5. You can see some experiments results: throughput diagrams, query results and difference on the freshness of the values in experiments/ directory.

Visualization of the DHT

While running the APIs you can also run a frontend app which periodically shows the contents of the nodes in the P2P network. You need to run python control-panel.py and access the visualization via your browser pressing the indicated link.

Contributors

• Cleopatra Dimaraki
• Nikolaos Papakonstantopoulos