README

Description

These are source codes for a web-based test on QoE of Internet.

This is a localhost version.

Setup

1. Install node.js from its official website

   if you are using Windows, make sure to click 'add to path' when installing.

   To test if the installation is successful, you can input

   node -v

   in your command line.

2. Download the zip file and unzip it. Locate to the folder:

   cd QoEProject

3. (Optional) Install all the dependencies:

   This is an optional step for those without node-modules folder. If you have downloaded the complete file, all the modules are already in the node-modules folder.

   npm install

4. Start the server on localhost:

   npm start
   or
   node app.js

5. Visit localhost:3000 on your website, you should see the instruction page.

   After finishing the test, the results will be stored in ./results/, the file name will be the MTurk ID.

Problems(solved)

1. Only one tester can proceed the test at the same time. This is because I used some variables to control the order of the webpages, videos, etc. If another tester visits the webpage, he will be asked to wait first. One big problem is that if one tester quits before finishing, then the server will keep waiting. I wonder if this problem can be solved by multi-process methods(each tester has a pid).

   An idea just came across my mind: can I use ctx to transfer these global variables? eg.

   ctx.video_order = video_order;
   ctx.count = count;
   ctx.result = result;
   

   This problem is fixed: the idea is using cookie, bind all the global variables to the cookie by using:

   ctx.cookies.set('name');
   ctx.cookies.get('name');
   

   Also need to add

   app.use(async (ctx, next) => {
   ctx.state.user = parseUser(ctx.cookies.get('name') || '');
   await next();
   });
   

   in app.js .

About data

1. The raw data collected from the website are .txt files, containing info about grades, order of videos, watching and decision time of each grade, and the content of the survey. I will up load them to ./raw_data/, you can load these data into npy files with process_data.py, which has already been done and the npy files are in ./data folder, so you may not need to deal with raw data. I have rejected unqualified results on MTurk, so all the results in the npy file are valid.

2. In the ./data folder, you can see all the npy files and plotting codes. Sorry for the confusing names of the npy files:

   • amazon: 001, 002, 003, 004
   • cnn: cnn, cnn_new
   • google: google, google_new
   • youtube: youtube, youtube_new

3. To plot a single curve for a website, eg. amazon, just run plot_amazon.py. To plot all the curves combined in one picture, run plot_combine.py. plot_diff.py plots the differential of the curves on every 2 points(you can modify to every 1 point). All the plotted results are in the ./figs folder.