@ayman

I finished cleaning up RESULTS.md, added some more limitations, and fixed some discrepancies.

I fixed my citations and also added a different section for people interested in running my program.

Commented through analyze.py.

I finished commenting through echo_client.py.

I commented through channel.py so it is easier to read the documentation and understand it.

Using pytest, I added a test_channel.py file that checks 3 of the functions in my code: make_channel, adding Bernoulli loss, and changing GE burst lengths.

FIxed readme and added to results.md

OK, next I made a new plot to analyze the missed packet deadline percentage for my latency ladder and jitter runs. We can see that all the latency ladders show a similar shape with a horizontal shift, while the jitter run has an S-shaped curve with an inflection point around 100 ms.

I made a new Python file that creates a new figure using matplotlib, and it measures the median and p99 RTT for my latency ladder. I will now add this into my RESULTS.md.

So I worked on fixing and updating my plot.py with some features. I added a title version, fixed the y-axis labeling, and then added a theoretical value using the definitions of GE loss and Bernoulli loss. Something we see is that in the real data there is a staircase step, due to burst values being only integers, while the theoretical value is a straight line. Here is a before and after.

Added sections 5–7 to RESULTS.md, which talk about the limitations, and I also talked about the .py file I made yesterday.

i added a new file that is supposed to check across all runs if the value in the csv matches with my decide function to check my seeds. Out of 60000 packets i only got one mismatch

I first added requirements.txt to my repo for people who want to rerun or add onto the experiment, and I also made sure to include instructions to repeat it in my README. Then I fixed some rounding errors in my summary.csv and also added a RESULTS.md that I have not finished yet.

I used matplotlib to make a graph of my burst results. The x-axis is the burst length (how many packets are lost in a row), and the y-axis is the percentage of bursts that were greater than or equal to the k value. You obviously see a declining trend for both, because it’s much harder for a random point to lose a lot of packets in a row. We see a big difference between Gilbert-Elliott and Bernoulli here, and the difference between the two packet loss calculation methods.

So now I worked on making another CSV as part of analyze.py, which counts how many bursts were in each run and the length and frequency of the bursts. A burst is basically how many packets were lost in a row. Now I am going to download matplotlib to plot it, see how my data and experiment actually work, and try to understand my results.

OK, I had to fix a few things with my analyze.py and summary.csv because it didn’t track lost packets or the parameters of the runs, so I used enumerate, slicing, and joining to get the right parameters for each run.

So over the past few days, I have been working on an analyze.py Python file that takes my CSV results from the 14 trials and basically combines all of it into one summary. Obviously it’s missing late and params, so I have to fix that and make a new one, but I had to learn a lot, and there was a lot of logic I did wrong in the beginning, so I’m glad I worked it out.

Today was a long day. I basically wrote a new Python file that connects to config.py and runs the server and client multiple times, and I ran a smoke test. I learned a lot of new things, like matrices, which keep all my tests, as well as parsing through argparse.

Today I created a config.py where I can set all the parameters for the experiments I can do, and I used it to connect channel.py to config.py. I also ran some tests of Bernoulli versus Gilbert-Elliott.