Install docker (and optionally compose V2 plugin - not the docker-compose!) and VSCode on your sytstem. Run the docker containers as non-root users...
Go to your favorite development folder on your local machine and run
git clone https://github.com/cengwins/ceng435.git
Open this folder (ceng435) in VSCode
Open a terminal in VSCode, under the ceng435 directory where the Dockerfile resides run
docker build -t ceng435 .
After the image is built you can directly run your containers or use docker compose pluging to run them:
You can run the following to get the server machine
docker run -t -i --rm --privileged --cap-add=NET_ADMIN --name ceng435server -v ./code:/app:rw ceng435:latest bash
and the following for the client machine
docker run -t -i --rm --privileged --cap-add=NET_ADMIN --name ceng435client -v ./code:/app:rw ceng435:latest bash
and you will be in your Ubuntu 22.04 Docker instance (python installed). Note that if you develop code in these Docker instances, if you stop the machine your code will be lost. That is why I recommend you to use Github to store your code and clone in the machine, and push your code to Github before shutting the Docker instances down. The other option is to work in the /app folder in your Docker instance is mounted to the "code" directory of your own machine.
IMPORTANT Note that the "code" folder on your local machine is mounted to the "/app" folder in the Docker instance (read/write mode). You can use these folders (they are the same in fact) to develop your code. Other than the /app folder, this tool does not guarantee any persistent storage: if you exit the Docker instance, all data will be lost.
After running the Ubuntu Docker, you can type "ip addr" to see your network configuration. Work on eth0.
Docker extension of vscode will be of great benefit to you.
In the server terminal, move to the "objects" folder and run
./generateobjects
to generate 10 small (10K) and 10 large (10M) objects together with their md5 checksums.
Some tc commands that may be of help to you can be found at https://man7.org/linux/man-pages/man8/tc-netem.8.html and https://www.cs.unm.edu/~crandall/netsfall13/TCtutorial.pdf
You will analyze the impact of delay, packet loss percentage, corrupt packet percentage, duplicate percentage, reorder percentage on the total time to download all 20 objects. You will plot figures for each parameter (delay, loss, ...) where the x-axis of the figure will have various values for these parameters and the y-axis will be the total time to download 20 objects. There will be two curves in each figure, one for TCP and the other curve for your UDP-based RDT implementation together with interleaving technique.
To start server and client containers:
docker compose up -d
To stop server and client containers:
docker compose down
Note that, if you orchestrate your containers using docker compose, the containers will have hostnames ("client" and "server") and DNS will be able to resolve them...
In one terminal, attach to the server container
docker exec -it server bash
In another terminal, attach to the client container
docker exec -it client bash
The local "code" folder is mapped to the "/app" folder in containers and the local "examples" folder is mapped to the "/examples" folder in the container. You can develop your code on your local folders on your own host machine, they will be immediately synchronized with the "/app" folder on containers. The volumes are created in read-write mode, so changes can be made both on the host or on the containers. You can run your code on the containers...
docker exec -it client bash
The local "code" folder is mapped to the "/app" folder in containers and the local "examples" folder is mapped to the "/examples" folder in the container. You can develop your code on your local folders on your own host machine, they will be immediately synchronized with the "/app" folder on containers. The volumes are created in read-write mode, so changes can be made both on the host or on the containers. You can run your code on the containers...