This repo includes the work for ECE356 Internet Traffic course project (Group 20)

• General info
• Deliverables
• CLI Setup
• Data Mining Setup

This project is a database client application for Internet Service Provider (ISP) network administrators using the Unicauca Network Flows Dataset, which is obtained from https://www.kaggle.com/jsrojas/labeled-network-traffic-flows-114-applications.

1. Internet_Traffic_ER_Model.pdf is the ER Model for the project
2. load_data.sql loads all data from the source dataset to a table
3. create_er.sql creates the relational schema for the ER model and load data from the table created by running load_data.sql
4. client_app.py is the main file for the CLI
5. create_account.py is the untility file that allows user to create an account before using the CLI
6. create_account.sql creates a table that stores all registered user account
7. handle_command.py is the utility file that handles commands entered by user
8. map_file.py stores some useful dictionaries and lists to be used by handle_command.py
9. data_mining.py is the main file for the data mining exercise
10. data_mining.sql has the queries needed to perform data mining exercise
11. Report.pdf contains detailed information about this project, including design, implementation, test plan, data mining, etc.
12. Video Demo.mp4 is a brief video demo that introduces the project

1. Before running this project, user needs to run load_data.sql and create_er.sql to populate the data tables
2. User needs to run create_account.sql to create a user account table
3. To run this project, run python3 client_app.py.
4. Then the user will be promoted to register a user account with appropriate privilege.
5. Once registered successfully, user needs to enter the user name and password again to login
6. Once logged in, user can start enter commands
7. User can exit the CLI by entering exit to the ternimal

1. To run the data mining exercise, run python3 data_mining.py
2. It will generate a plot which shows how usage frequency of web services evolves during different hours of a day