\textcolor{red}{Our first protocol based GLPK optimization solver is declined into four versions: MuDiLCO-1, MuDiLCO-3, MuDiLCO-5,
and MuDiLCO-7, corresponding respectively to $T=1,3,5,7$ ($T$ the number of rounds in one sensing period).
-The second protocol based based GLPK optimization solver with time limit is declined into four versions: TL-MuDiLCO-1, TL-MuDiLCO-3, TL-MuDiLCO-5, and TL-MuDiLCO-7. Table \ref{tl} shows time limit values for TL-MuDiLCO protocol versions. After extensive experiments, we chose the values that explained in Table \ref{tl} because they gave the best results. In Table \ref{tl}, "NO" refers to apply the GLPK solver without time limit because we did not find improvement on the results of MuDiLCO protocol with the time limit}.
+The second protocol based based GLPK optimization solver with time limit is declined into four versions: TL-MuDiLCO-1, TL-MuDiLCO-3, TL-MuDiLCO-5, and TL-MuDiLCO-7. Table \ref{tl} shows time limit values for TL-MuDiLCO protocol versions. After extensive experiments, we chose the values that explained in Table \ref{tl} because they gave the best results. In these experiments, we started with the average execution time of the corresponding MuDiLCO version and network size divided by 3 as a time limit. After that, we increase these values until reaching the best results. In fact, selecting the optimal values for the time limits can be investigated in future. In Table \ref{tl}, "NO" refers to apply the GLPK solver without time limit because we did not find improvement on the results of MuDiLCO protocol with the time limit. }.
\begin{table}[ht]
\caption{Time limit values for TL-MuDiLCO protocol versions }
\hline
100 & NO & NO & NO & NO \\
\hline
-150 & NO & 0.006 & NO & 0.03 \\
+150 & NO & NO & NO & 0.03 \\
\hline
-200 & 0.0035 & 0.0094 & 0.020 & 0.06 \\
+200 & NO & 0.0094 & 0.020 & 0.06 \\
\hline
- 250 & 0.0055 & 0.013 & 0.03 & 0.08 \\
+ 250 & NO & 0.013 & 0.03 & 0.08 \\
\hline
\end{tabular}
