Week 9 Review: 7/30 - 8/3

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At the start of this week I tried to clean and analyze more recent Tstat logs from January and July of this year. To my surprise, these files were formatted differently from my previous files which meant I had to clean and compile them differently as well. This posed many unexpected problems that took much longer to solve than I first imagined. Also planned for the week was to add a way to identify the "normal" cluster to the algorithm and perform quantitative analysis on the similarities of the calculated sequences with the log(throughput). All at the same time, this content needed to be put into my poster for the intern poster session by noon on Friday. After cleaning, I tried to add the cluster identification step to the algorithm. I was running behind, so without finishing it I moved on to calculating quantitative similarity metrics. I didn't want to consider the similarity of the sequences when throughput is high (because our values turn out to be low) so I took the Root Mean Square Error of the calculated sequence for points where throughput is less than 1 Mb/s.

S2C
S2C Recommended
C2S relevant
no_ports
RMS Error
0.2057
0.1962
0.2661
0.2035

Results of the RMS Error show that the S2C Recommended feature subset performed the best.
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