From: couturie Date: Tue, 22 Sep 2015 12:41:10 +0000 (+0200) Subject: Merge branch 'master' of ssh://bilbo.iut-bm.univ-fcomte.fr/JournalMultiPeriods X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/JournalMultiPeriods.git/commitdiff_plain/ddecf65df4863c8c486fb40a1ffe20d71262ae54?hp=45bf406e89296352827213ed99316750d1e720d8 Merge branch 'master' of ssh://bilbo.iut-bm.univ-fcomte.fr/JournalMultiPeriods --- diff --git a/F/EC50.eps b/F/EC50.eps index 63ba620..b8975a1 100644 --- a/F/EC50.eps +++ b/F/EC50.eps @@ -2,7 +2,7 @@ %%BoundingBox: 53 53 545 402 %%HiResBoundingBox: 54 53.5 544.5 401.5 %%Creator: gnuplot 4.6 patchlevel 0 -%%CreationDate: Tue Sep 8 11:00:48 2015 +%%CreationDate: Tue Sep 22 14:17:39 2015 %%EndComments % EPSF created by ps2eps 1.68 %%BeginProlog @@ -513,7 +513,7 @@ SDict begin [ /Author (ali) % /Producer (gnuplot) % /Keywords () - /CreationDate (Tue Sep 8 11:00:48 2015) + /CreationDate (Tue Sep 22 14:17:39 2015) /DOCINFO pdfmark end } ifelse @@ -799,11 +799,11 @@ LTb 2.000 UL LT0 0.00 0.55 0.55 C LCb setrgbcolor -1502 3392 M +1756 3392 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-1)] ] -36.7 MRshow LT0 -0.00 0.55 0.55 C 1568 3392 M +0.00 0.55 0.55 C 1822 3392 M 327 0 V 1029 1269 M 847 257 V @@ -815,18 +815,18 @@ LT0 2723 1686 TriUF 3570 1804 TriUF 4417 1894 TriUF -1731 3392 TriUF +1985 3392 TriUF % End plot #1 % Begin plot #2 1.000 UP 2.000 UL LT1 0.50 0.00 0.00 C LCb setrgbcolor -1502 3282 M +1756 3282 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-3)] ] -36.7 MRshow LT1 -0.50 0.00 0.00 C 1568 3282 M +0.50 0.00 0.00 C 1822 3282 M 327 0 V 1029 1409 M 847 150 V @@ -838,41 +838,41 @@ LT1 2723 1681 Star 3570 1767 Star 4417 1829 Star -1731 3282 Star +1985 3282 Star % End plot #2 % Begin plot #3 1.000 UP 2.000 UL LT2 0.00 0.00 0.55 C LCb setrgbcolor -1502 3172 M +1756 3172 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-5)] ] -36.7 MRshow LT2 -0.00 0.00 0.55 C 1568 3172 M +0.00 0.00 0.55 C 1822 3172 M 327 0 V 1029 1348 M 847 136 V 847 171 V 847 30 V -847 163 V +847 121 V 1029 1348 CircleF 1876 1484 CircleF 2723 1655 CircleF 3570 1685 CircleF -4417 1848 CircleF -1731 3172 CircleF +4417 1806 CircleF +1985 3172 CircleF % End plot #3 % Begin plot #4 1.000 UP 2.000 UL LT3 0.00 0.39 0.00 C LCb setrgbcolor -1502 3062 M +1756 3062 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-7)] ] -36.7 MRshow LT3 -0.00 0.39 0.00 C 1568 3062 M +0.00 0.39 0.00 C 1822 3062 M 327 0 V 1029 1311 M 847 202 V @@ -884,18 +884,18 @@ LT3 2723 1632 DiaF 3570 1740 DiaF 4417 1812 DiaF -1731 3062 DiaF +1985 3062 DiaF % End plot #4 % Begin plot #5 1.000 UP 2.000 UL LT4 0.49 0.99 0.00 C LCb setrgbcolor -1502 2952 M -[ [(Helvetica) 110.0 0.0 true true 0 (old-MuDiLCO-7)] +1756 2952 M +[ [(Helvetica) 110.0 0.0 true true 0 (Unlimited-MuDiLCO-7)] ] -36.7 MRshow LT4 -0.49 0.99 0.00 C 1568 2952 M +0.49 0.99 0.00 C 1822 2952 M 327 0 V 1029 1311 M 847 202 V @@ -907,18 +907,18 @@ LT4 2723 1685 Box 3570 2116 Box 4417 2692 Box -1731 2952 Box +1985 2952 Box % End plot #5 % Begin plot #6 1.000 UP 2.000 UL LT5 1.00 0.27 0.00 C LCb setrgbcolor -1502 2842 M +1756 2842 M [ [(Helvetica) 110.0 0.0 true true 0 (DESK)] ] -36.7 MRshow LT5 -1.00 0.27 0.00 C 1568 2842 M +1.00 0.27 0.00 C 1822 2842 M 327 0 V 1029 2092 M 847 170 V @@ -930,18 +930,18 @@ LT5 2723 2481 BoxF 3570 2727 BoxF 4417 3160 BoxF -1731 2842 BoxF +1985 2842 BoxF % End plot #6 % Begin plot #7 1.000 UP 2.000 UL LT6 0.50 0.00 0.50 C LCb setrgbcolor -1502 2732 M +1756 2732 M [ [(Helvetica) 110.0 0.0 true true 0 (GAF)] ] -36.7 MRshow LT6 -0.50 0.00 0.50 C 1568 2732 M +0.50 0.00 0.50 C 1822 2732 M 327 0 V 1029 1793 M 847 183 V @@ -953,7 +953,7 @@ LT6 2723 2068 PentF 3570 2156 PentF 4417 2253 PentF -1731 2732 PentF +1985 2732 PentF % End plot #7 1.000 UL LTb diff --git a/F/EC50.pdf b/F/EC50.pdf index b9f462d..5bc232a 100644 Binary files a/F/EC50.pdf and b/F/EC50.pdf differ diff --git a/F/EC95.eps b/F/EC95.eps index e017cab..3930f19 100644 --- a/F/EC95.eps +++ b/F/EC95.eps @@ -2,7 +2,7 @@ %%BoundingBox: 53 53 545 399 %%HiResBoundingBox: 54 53.5 544.5 398 %%Creator: gnuplot 4.6 patchlevel 0 -%%CreationDate: Tue Sep 8 11:02:10 2015 +%%CreationDate: Tue Sep 22 14:25:15 2015 %%EndComments % EPSF created by ps2eps 1.68 %%BeginProlog @@ -513,7 +513,7 @@ SDict begin [ /Author (ali) % /Producer (gnuplot) % /Keywords () - /CreationDate (Tue Sep 8 11:02:10 2015) + /CreationDate (Tue Sep 22 14:25:15 2015) /DOCINFO pdfmark end } ifelse @@ -839,11 +839,11 @@ LTb 2.000 UL LT0 0.00 0.55 0.55 C LCb setrgbcolor -1502 3398 M +1756 3398 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-1)] ] -36.7 MRshow LT0 -0.00 0.55 0.55 C 1568 3398 M +0.00 0.55 0.55 C 1822 3398 M 327 0 V 1029 1199 M 847 128 V @@ -855,18 +855,18 @@ LT0 2723 1412 TriUF 3570 1484 TriUF 4417 1554 TriUF -1731 3398 TriUF +1985 3398 TriUF % End plot #1 % Begin plot #2 1.000 UP 2.000 UL LT1 0.50 0.00 0.00 C LCb setrgbcolor -1502 3288 M +1756 3288 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-3)] ] -36.7 MRshow LT1 -0.50 0.00 0.00 C 1568 3288 M +0.50 0.00 0.00 C 1822 3288 M 327 0 V 1029 1195 M 847 116 V @@ -878,41 +878,41 @@ LT1 2723 1383 Star 3570 1435 Star 4417 1486 Star -1731 3288 Star +1985 3288 Star % End plot #2 % Begin plot #3 1.000 UP 2.000 UL LT2 0.00 0.00 0.55 C LCb setrgbcolor -1502 3178 M +1756 3178 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-5)] ] -36.7 MRshow LT2 -0.00 0.00 0.55 C 1568 3178 M +0.00 0.00 0.55 C 1822 3178 M 327 0 V 1029 1187 M 847 123 V 847 73 V 847 20 V -847 119 V +847 68 V 1029 1187 CircleF 1876 1310 CircleF 2723 1383 CircleF 3570 1403 CircleF -4417 1522 CircleF -1731 3178 CircleF +4417 1471 CircleF +1985 3178 CircleF % End plot #3 % Begin plot #4 1.000 UP 2.000 UL LT3 0.00 0.39 0.00 C LCb setrgbcolor -1502 3068 M +1756 3068 M [ [(Helvetica) 110.0 0.0 true true 0 (MuDiLCO-7)] ] -36.7 MRshow LT3 -0.00 0.39 0.00 C 1568 3068 M +0.00 0.39 0.00 C 1822 3068 M 327 0 V 1029 1191 M 847 127 V @@ -924,18 +924,18 @@ LT3 2723 1372 DiaF 3570 1435 DiaF 4417 1480 DiaF -1731 3068 DiaF +1985 3068 DiaF % End plot #4 % Begin plot #5 1.000 UP 2.000 UL LT4 0.49 0.99 0.00 C LCb setrgbcolor -1502 2958 M -[ [(Helvetica) 110.0 0.0 true true 0 (old-MuDiLCO-7)] +1756 2958 M +[ [(Helvetica) 110.0 0.0 true true 0 (Unlimited-MuDiLCO-7)] ] -36.7 MRshow LT4 -0.49 0.99 0.00 C 1568 2958 M +0.49 0.99 0.00 C 1822 2958 M 327 0 V 1029 1191 M 847 127 V @@ -947,18 +947,18 @@ LT4 2723 1419 Box 3570 1927 Box 4417 2865 Box -1731 2958 Box +1985 2958 Box % End plot #5 % Begin plot #6 1.000 UP 2.000 UL LT5 1.00 0.27 0.00 C LCb setrgbcolor -1502 2848 M +1756 2848 M [ [(Helvetica) 110.0 0.0 true true 0 (DESK)] ] -36.7 MRshow LT5 -1.00 0.27 0.00 C 1568 2848 M +1.00 0.27 0.00 C 1822 2848 M 327 0 V 1029 1672 M 847 107 V @@ -970,18 +970,18 @@ LT5 2723 2054 BoxF 3570 2253 BoxF 4417 2503 BoxF -1731 2848 BoxF +1985 2848 BoxF % End plot #6 % Begin plot #7 1.000 UP 2.000 UL LT6 0.50 0.00 0.50 C LCb setrgbcolor -1502 2738 M +1756 2738 M [ [(Helvetica) 110.0 0.0 true true 0 (GAF)] ] -36.7 MRshow LT6 -0.50 0.00 0.50 C 1568 2738 M +0.50 0.00 0.50 C 1822 2738 M 327 0 V 1029 1495 M 847 350 V @@ -993,7 +993,7 @@ LT6 2723 1886 PentF 3570 1918 PentF 4417 2008 PentF -1731 2738 PentF +1985 2738 PentF % End plot #7 1.000 UL LTb diff --git a/F/EC95.pdf b/F/EC95.pdf index 2dbef9a..eb5022d 100644 Binary files a/F/EC95.pdf and b/F/EC95.pdf differ diff --git a/F/LT50.pdf b/F/LT50.pdf index 5f94eda..e14f97d 100644 Binary files a/F/LT50.pdf and b/F/LT50.pdf differ diff --git a/F/LT95.pdf b/F/LT95.pdf index 8af43e2..7ee8481 100644 Binary files a/F/LT95.pdf and b/F/LT95.pdf differ diff --git a/F/T.pdf b/F/T.pdf index c442be4..a0a3185 100644 Binary files a/F/T.pdf and b/F/T.pdf differ diff --git a/article.tex b/article.tex index 42d7890..384ab08 100644 --- a/article.tex +++ b/article.tex @@ -437,6 +437,7 @@ one-hop neighbors as the primary criterion to reduce energy consumption due to the communications. \subsection{Decision phase} +\label{decision} Each WSNL will \textcolor{blue}{solve an integer program to select which cover sets will be activated in the following sensing phase to cover the subregion @@ -947,26 +948,28 @@ consumption point of view. The other approaches have a high energy consumption due to activating a larger number of redundant nodes as well as the energy consumed during the different status of the sensor node. -% TO BE CONTINUED \textcolor{blue}{Energy consumption increases with the size of the networks and - the number of rounds. The curve Unlimited-MuDiLCO-7 shows that energy + the number of rounds. The curve Unlimited-MuDiLCO-7 shows that energy consumption due to the time spent to solve the integer program to optimality increases drastically with the size of the network. When the resolution time is limited for large network sizes, the energy consumption remains of the same - order whatever the MuDiLCO version.} - + order whatever the MuDiLCO version. As can be seen with MuDiLCO-7.} \subsection{Execution time} \label{et} -We observe the impact of the network size and of the number of rounds on the +We observe the impact of the network size and of the number of rounds on the computation time. Figure~\ref{fig77} gives the average execution times in -seconds (needed to solve optimization problem) for different values of $T$. The modeling language for Mathematical Programming (AMPL)~\cite{AMPL} is employed to generate the Mixed Integer Linear Program instance in a standard format, which is then read and solved by the optimization solver GLPK (GNU linear Programming Kit available in the public domain) \cite{glpk} through a Branch-and-Bound method. The -original execution time is computed on a laptop DELL with Intel Core~i3~2370~M -(2.4 GHz) processor (2 cores) and the MIPS (Million Instructions Per Second) -rate equal to 35330. To be consistent with the use of a sensor node with Atmels -AVR ATmega103L microcontroller (6 MHz) and a MIPS rate equal to 6 to run the -optimization resolution, this time is multiplied by 2944.2 $\left( -\frac{35330}{2} \times \frac{1}{6} \right)$ and reported on Figure~\ref{fig77} +seconds (needed to solve optimization problem) for different values of $T$. The +modeling language for Mathematical Programming (AMPL)~\cite{AMPL} is employed to +generate the Mixed Integer Linear Program instance in a standard format, which +is then read and solved by the optimization solver GLPK (GNU linear Programming +Kit available in the public domain) \cite{glpk} through a Branch-and-Bound +method. The original execution time is computed on a laptop DELL with Intel +Core~i3~2370~M (2.4 GHz) processor (2 cores) and the MIPS (Million Instructions +Per Second) rate equal to 35330. To be consistent with the use of a sensor node +with Atmels AVR ATmega103L microcontroller (6 MHz) and a MIPS rate equal to 6 to +run the optimization resolution, this time is multiplied by 2944.2 $\left( +\frac{35330}{2} \times \frac{1}{6} \right)$ and reported on Figure~\ref{fig77} for different network sizes. \begin{figure}[ht!] @@ -977,87 +980,84 @@ for different network sizes. \end{figure} As expected, the execution time increases with the number of rounds $T$ taken -into account to schedule the sensing phase. The times obtained for $T=1,3$ -or $5$ seem bearable, but for $T=7$ they become quickly unsuitable for a sensor -node, especially when the sensor network size increases. Again, we can notice -that if we want to schedule the nodes activities for a large number of rounds, -we need to choose a relevant number of subregions in order to avoid a complicated -and cumbersome optimization. On the one hand, a large value for $T$ permits to -reduce the energy-overhead due to the three pre-sensing phases, on the other -hand a leader node may waste a considerable amount of energy to solve the -optimization problem. - -%While MuDiLCO-1, 3, and 5 solves the optimization process with suitable execution times to be used on wireless sensor network because it distributed on larger number of small subregions as well as it is used acceptable number of round(s) T. We think that in distributed fashion the solving of the optimization problem to produce T rounds in a subregion can be tackled by sensor nodes. Overall, to be able to deal with very large networks, a distributed method is clearly required. +into account to schedule the sensing phase. \textcolor{blue}{Obviously, the + number of variables and constraints of the integer program increases with $T$, + as was explained in section~\ref{decision} The times obtained for $T=1,3$ or + $5$ seem bearable. But for $T=7$, without any limitation of the time, they + become quickly unsuitable for a sensor node, especially when the sensor + network size increases as demonstrated by Unlimited-MuDiLCO-7. Notice that + for 250 nodes, we also limited the execution time for $T=5$, otherwise the + execution time would have been above MuDiLCO-7. On the one hand, a large + value for $T$ permits to reduce the energy-overhead due to the three + pre-sensing phases, on the other hand a leader node may waste a considerable + amount of energy to solve the optimization problem. Thus, limiting the time + resolution for large instances allows to reduce the energy consumption without + any impact on the coverage quality.} \subsection{Network lifetime} The next two figures, Figures~\ref{fig8}(a) and \ref{fig8}(b), illustrate the network lifetime for different network sizes, respectively for $Lifetime_{95}$ -and $Lifetime_{50}$. Both figures show that the network lifetime increases +and $Lifetime_{50}$. Both figures show that the network lifetime increases together with the number of sensor nodes, whatever the protocol, thanks to the -node density which results in more and more redundant nodes that can be +node density which results in more and more redundant nodes that can be deactivated and thus save energy. Compared to the other approaches, our MuDiLCO -protocol maximizes the lifetime of the network. In particular the gain in -lifetime for a coverage over 95\% is greater than 38\% when switching from GAF -to MuDiLCO-3. The slight decrease that can be observed for MuDiLCO-7 in case -of $Lifetime_{95}$ with large wireless sensor networks results from the -difficulty of the optimization problem to be solved by the integer program. -This point was already noticed in subsection \ref{subsec:EC} devoted to the -energy consumption, since network lifetime and energy consumption are directly -linked. -%\textcolor{red}{As can be seen in these figures, the lifetime increases with the size of the network, and it is clearly largest for the MuDiLCO -%and the GA-MuDiLCO protocols. GA-MuDiLCO prolongs the network lifetime obviously in comparison with both DESK and GAF, as well as the MuDiLCO-7 version for $lifetime_{95}$. However, comparison shows that MuDiLCO protocol and GA-MuDiLCO protocol, which use distributed optimization over the subregions are the best ones because they are robust to network disconnection during the network lifetime as well as they consume less energy in comparison with other approaches.} +protocol maximizes the lifetime of the network. In particular the gain in +lifetime for a coverage over 95\%, and a network of 250~nodes, is greater than +38\% when switching from GAF to MuDiLCO-5. +%The lower performance that can be observed for MuDiLCO-7 in case +%of $Lifetime_{95}$ with large wireless sensor networks results from the +%difficulty of the optimization problem to be solved by the integer program. +%This point was already noticed in subsection \ref{subsec:EC} devoted to the +%energy consumption, since network lifetime and energy consumption are directly +%linked. +\textcolor{blue}{Overall, it appears clearly that computing a scheduling for + several rounds is possible and relevant, providing that the execution time to + solve the optimization problem for large instances is limited. Notice that + rather than limiting the execution time, similar results might be obtained by + replacing the computation of the exact solution with the finding of a + suboptimal one using a heuristic approach. For our simulation setup and + considering the different metrics, MuDiLCO-5 seems to be the most suited + method in comparison with MuDiLCO-7.} + \begin{figure}[t!] \centering \begin{tabular}{cl} - \parbox{9.5cm}{\includegraphics[scale=0.5]{F/LT95.pdf}} & (a) \\ + \parbox{9.5cm}{\includegraphics[scale=0.5125]{F/LT95.pdf}} & (a) \\ \verb+ + \\ - \parbox{9.5cm}{\includegraphics[scale=0.5]{F/LT50.pdf}} & (b) + \parbox{9.5cm}{\includegraphics[scale=0.5125]{F/LT50.pdf}} & (b) \end{tabular} \caption{Network lifetime for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$} \label{fig8} \end{figure} -% By choosing the best suited nodes, for each round, by optimizing the coverage and lifetime of the network to cover the area of interest with a maximum number rounds and by letting the other nodes sleep in order to be used later in next rounds, our MuDiLCO protocol efficiently prolonges the network lifetime. - -%In Figure~\ref{fig8}, Comparison shows that our MuDiLCO protocol, which are used distributed optimization on the subregions with the ability of producing T rounds, is the best one because it is robust to network disconnection during the network lifetime as well as it consume less energy in comparison with other approaches. It also means that distributing the protocol in each sensor node and subdividing the sensing field into many subregions, which are managed independently and simultaneously, is the most relevant way to maximize the lifetime of a network. - - -%We see that our MuDiLCO-7 protocol results in execution times that quickly become unsuitable for a sensor network as well as the energy consumption seems to be huge because it used a larger number of rounds T during performing the optimization decision in the subregions, which is led to decrease the network lifetime. On the other side, our MuDiLCO-1, 3, and 5 protocol seems to be more efficient in comparison with other approaches because they are prolonged the lifetime of the network more than DESK and GAF. - - \section{Conclusion and future works} \label{sec:conclusion} -We have addressed the problem of the coverage and of the lifetime optimization in -wireless sensor networks. This is a key issue as sensor nodes have limited +We have addressed the problem of the coverage and of the lifetime optimization +in wireless sensor networks. This is a key issue as sensor nodes have limited resources in terms of memory, energy, and computational power. To cope with this -problem, the field of sensing is divided into smaller subregions using the +problem, the field of sensing is divided into smaller subregions using the concept of divide-and-conquer method, and then we propose a protocol which -optimizes coverage and lifetime performances in each subregion. Our protocol, -called MuDiLCO (Multiround Distributed Lifetime Coverage Optimization) combines +optimizes coverage and lifetime performances in each subregion. Our protocol, +called MuDiLCO (Multiround Distributed Lifetime Coverage Optimization) combines two efficient techniques: network leader election and sensor activity -scheduling. -%, where the challenges -%include how to select the most efficient leader in each subregion and -%the best cover sets %of active nodes that will optimize the network lifetime -%while taking the responsibility of covering the corresponding -%subregion using more than one cover set during the sensing phase. -The activity scheduling in each subregion works in periods, where each period -consists of four phases: (i) Information Exchange, (ii) Leader Election, (iii) -Decision Phase to plan the activity of the sensors over $T$ rounds, (iv) Sensing -Phase itself divided into $T$ rounds. - -Simulations results show the relevance of the proposed protocol in terms of +scheduling. The activity scheduling in each subregion works in periods, where +each period consists of four phases: (i) Information Exchange, (ii) Leader +Election, (iii) Decision Phase to plan the activity of the sensors over $T$ +rounds, (iv) Sensing Phase itself divided into $T$ rounds. + +Simulations results show the relevance of the proposed protocol in terms of lifetime, coverage ratio, active sensors ratio, energy consumption, execution time. Indeed, when dealing with large wireless sensor networks, a distributed -approach, like the one we propose, allows to reduce the difficulty of a single +approach, like the one we propose, allows to reduce the difficulty of a single global optimization problem by partitioning it in many smaller problems, one per -subregion, that can be solved more easily. Nevertheless, results also show that -it is not possible to plan the activity of sensors over too many rounds, because -the resulting optimization problem leads to too high resolution times and thus to -an excessive energy consumption. +subregion, that can be solved more easily. \textcolor{blue}{ Furthermore, + results also show that to plan the activity of sensors for large network + sizes, an approach to obtain a near optimal solution is needed. Indeed, an + exact resolution of the resulting optimization problem leads to prohibitive + computation times and thus to an excessive energy consumption.} %In future work, we plan to study and propose adjustable sensing range coverage optimization protocol, which computes all active sensor schedules in one time, by using %optimization methods. This protocol can prolong the network lifetime by minimizing the number of the active sensor nodes near the borders by optimizing the sensing range of sensor nodes. diff --git a/reponse.tex b/reponse.tex index 3b1c8e2..0e45ef2 100644 --- a/reponse.tex +++ b/reponse.tex @@ -170,8 +170,7 @@ to improve the results of MuDiLCO-7 in particular.\\ the paper is organized as follows'' should mention the content of Section 5. } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed. Section 5 is included - as subsection 4.5 within section 4.}}\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 3 The sentence ``the centralized approaches usually suffer from the scalability problem, making them less competitive as the @@ -187,7 +186,7 @@ to improve the results of MuDiLCO-7 in particular.\\ should provide at least one reference about the aforementioned study.}\\ \textcolor{blue}{\textbf{\textsc{Answer:} Right. We have included a section - (section~4.4) dedicated to the choice and the number of primary points.}}\\ + (section~5.1) dedicated to the choice and the number of primary points.}}\\ \noindent {\ding{90} Page 6, Figure 1: All rounds seem to have the same duration. This should be stated explicitly, and justified (in column