# A Multi-Parameter Comprehensive Optimized Algorithm for MPTCP Networks
## 5 Result Analysis
### SRL to HU
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Scenario**} & \multirow{2}{*}{**From ISP**} & \multirow{2}{*}{**To ISP**} & \multirow{2}{*}{**Subflow**} & \multicolumn{6}{c}{**\(\boldsymbol{\Omega}\)**} & \multirow{2}{*}{\(\boldsymbol{\Omega}\)**} \\ \cline{3-4} \cline{6-10}  & & & & **Cubic** & & **OLIA** & & **Hyla** & **Reno** & **Scalable** & **Vegas** \\ \hline \multirow{6}{*}{SRL-HU} & Kvantel & CERNET & K-C & 0.496 & 0.376 & 0.396 & 0.469 & 0.292 & 0.356 \\  & Kvantel & CnUnion & K-CU & 0.248 & 0.359 & 0.174 & \(-0.027\) & 0.19 & 0.135 \\  & PowerTech & CERNET & P-C & \(-0.313\) & 0.098 & \(-23.667\) & 0.174 & \(-0.324\) & 0.086 \\  & PowerTech & CnUnion & P-CU & 0.184 & 0.172 & \(-0.366\) & \(-0.496\) & 0.24 & 0.077 \\  & Telenor & CERNET & T-C & 0.032 & \(-0.54\) & \(-40.713\) & 0.14 & 0.057 & 0.08 \\  & Telenor & CnUnion & T-CU & 0.046 & 0.105 & \(-13.235\) & 0.085 & 0.02 & 0.057 \\  & Uninett & CERNET & U-C & 0.239 & 0.305 & 0.209 & 0.235 & 0.301 & 0.325 \\  & Uninett & CnUnion & U-CU & 0.063 & 0.113 & 0.258 & 0.165 & 0.072 & 0.189 \\ \hline \multirow{6}{*}{UNIS-HiN} & Telenor & Broadnet & T-B & \(-0.014\) & 0.017 & \(-0.019\) & 0.061 & \(-0.154\) & 0.014 \\  & Telenor & PowerTech & T-P & \(-0.063\) & 0.002 & 0.001 & 0.028 & \(-0.03\) & \(-0.004\) \\ \cline{1-1}  & Telenor & Uninett & T-U & \(-0.011\) & \(-0.047\) & \(-0.013\) & \(-0.034\) & 0.036 & 0.027 \\ \cline{1-1}  & Uninett & Broadnet & U-B & \(-0.046\) & 0.025 & \(-0.025\) & 0.02 & \(-0.008\) & 0.094 \\ \cline{1-1}  & Uninett & PowerTech & U-P & \(-0.075\) & 0.054 & \(-0.003\) & \(-0.001\) & 0.004 & \(-0.13\) \\ \cline{1-1}  & Uninett & Uninett & U-U & 0.897 & 0.916 & 0.921 & 0.92 & 0.923 & 0.852 \\ \hline \multirow{2}{*}{UiT-HAW} & PowerTech & DFN & P-D & 0.59 & 0.61 & 0.55 & 0.57 & 0.61 & 0.58 \\ \cline{1-1}  & Telenor & DFN & T-D & 0.44 & 0.46 & 0.44 & 0.43 & 0.45 & 0.44 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Impact factors for SRL to HU, UNIS to HiN, and UiT to HAW. \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**CC**} & \multicolumn{2}{c}{**Optional Subflow Subset**} \\ \cline{2-3} \cline{3-4}  & **SRL-HU** & **UNIS-HiN** & **UiT-HAW** \\ \hline \multirow{2}{*}{Cubic} & \{K-C, K-CU, P-CU, T-C, T-CU, \\  & U-C, U-CU\} & \{P-D, T-D\} \\ \multirow{2}{*}{OLIA} & \{K-C, K-CU, P-C, P-CU, T-CU, \\  & U-C, U-CU\} & \{P-D, T-D\} \\ \multirow{2}{*}{Hybla} & \{K-C, K-CU, U-U, U-CU, \\  & Reno & \{K-C, P-C, T-CU, U-C\} & \{T-B, T-U, U-U\} & \{P-D, T-D\} \\ \multirow{2}{*}{Scalable} & \{K-C, K-CU, P-CU, T-C, T-CU, \\  & U-C, U-CU\} & \{T-U, U-P, U-U\} & \{P-D, T-D\} \\ \multirow{2}{*}{Vegas} & \{K-C, K-CU, P-C, P-CU, T-C, \\  & T-CU, U-C, U-CU\} & \{T-B, T-U, U-U\} & \{P-D, T-D\} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Optional subflow subsets for SRL to HU, UNIS to HiN, and UiT to HAW. Table 4 shows that the R-square value 0.80 is less than 0.90, due to the volatility of the data. A detailed analysis of the SRL-HU site connectivity is presented in [26]: There is a significant performance variance of the underlying intercontinental connections during the day, depending on network usage during office hours, etc. The \(p\)-value of each variable is less than 0.00001. For example, \(p\)-value of coefficient 4.17 is \(<\)0.00001, indicating that there is less than 0.00001 probability that impact of variable \(bs\) on \(tp\) is null, i.e., buffer size does significantly affect throughput. Nevertheless, Equation (13) is still the best model we may get. From Table 4, it is easy to calculate the maximum throughput which is \(tp_{\text{max}}=80.27\) Mbit/s, and the corresponding BS is \(bs=18.12\) MiB, PM is PCDC and CC is Hybla. Considering Equation (10), with sacrificing \(\delta=7\%\) the throughput, the throughput is 74.65 Mbit/s, and the corresponding buffer size is 12.36 MiB. \(7\%\) is the empirical value obtained through many experiments.