# Multi Swarm Optimization Based Clustering with Tabu Search in Wireless Sensor Network
## 4 Results and Discussion  
In this section, the proposed MSO-Tabu approach is critically evaluated by comparing its performance with GA, DE, Tabu search, and MSO based clustering. The numerical experiments are conducted on a Dell Optiplex(tm) 3020 personal computer with Intel Core i7-4770 3.4 GHz processor along with 8 MB Cache and integrated Intel graphics, 16 GB RAM, 1 TB HDD, and Windows 10 operating system. Matlab R2019a is used as the simulation environment. The parameters of the network used are reported in Table 1.  
The experiments are carried out using 200 to 1200 nodes and 0 to 700 rounds. The number of clusters created, average end-to-end delay in seconds, average packet loss rate, lifetime computation, and average energy dissipated in joules as shown in Tables 2-6 and Figures 1-5. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Description** \\ \hline Transmission Range & 30 m \\ Sensing range of node & 10 m \\ Initial energy of node & 40 Joules \\ Bandwidth of node & 50 kbps \\ Size of network & 300 square meters \\ Size of each region & 75 square meters \\ Packet transmission rate & 30 packets/seconds \\ Mobility model & Random waypoint \\ Simulation time & 35 min \\ Tx energy & 16 milliWait \\ Rx energy & 12 milliWait \\ Power intensity & \(-20\) dBm to 12 dBm \\ Mobility & 0.5 m/s to 3.5 m/s \\ Size of packets & 8, 16, 32, 64, 128, 256 bytes \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters of the network. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Number of Rounds** & **GA** & **DE** & **Tabu** & **MSO Based Clustering** & **MSO-Tabu** \\ \hline
0 & 100 & 100 & 100 & 100 & 100 \\
100 & 96 & 100 & 97 & 100 & 100 \\
200 & 92 & 93 & 92 & 93 & 94 \\
300 & 83 & 87 & 84 & 88 & 90 \\
400 & 72 & 73 & 72 & 73 & 79 \\
500 & 50 & 58 & 51 & 57 & 62 \\
600 & 22 & 16 & 22 & 15 & 31 \\
700 & 1 & 4 & 1 & 4 & 11 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Average energy dissipated in Joules for MSO-Tabu. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number of Nodes** & **GA** & **DE** & **Tabu** & **MSO Based Clustering** & **MSO-Tabu** \\ \hline
200 & 10.07 & 9.06 & 9.04 & 8.56 & 7.95 \\
400 & 15.1 & 12.51 & 13.6 & 12.32 & 11.63 \\
600 & 16.24 & 12.06 & 15.19 & 12.9 & 12.18 \\
800 & 22.01 & 19.51 & 20.09 & 19.2 & 17.67 \\
1000 & 27.11 & 26.11 & 26.42 & 26.09 & 24.54 \\
1200 & 35.68 & 28.56 & 34.35 & 29.27 & 27.69 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Average packet loss rate for MSO-Tabu. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number of Nodes** & **GA** & **DE** & **Tabu** & **MSO Based Clustering** & **MSO-Tabu** \\ \hline
200 & 10 & 12 & 11 & 12 & 13 \\
400 & 16 & 16 & 16 & 17 & 18 \\
600 & 26 & 27 & 27 & 27 & 28 \\
800 & 29 & 30 & 28 & 30 & 31 \\
1000 & 29 & 32 & 29 & 32 & 33 \\
1200 & 35 & 39 & 36 & 39 & 39 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Number of clusters formed for MSO-Tabu. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number of Rounds** & **GA** & **DE** & **Tabu** & **MSO Based Clustering** & **MSO-Tabu** \\ \hline
0 & 100 & 100 & 100 & 100 \\
100 & 96 & 100 & 97 & 100 & 100 \\
200 & 92 & 93 & 92 & 93 & 94 \\
300 & 83 & 87 & 84 & 88 & 90 \\
400 & 72 & 73 & 72 & 73 & 79 \\
500 & 50 & 58 & 51 & 57 & 62 \\
600 & 22 & 16 & 22 & 15 & 31 \\
700 & 1 & 4 & 1 & 4 & 11 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Lifetime computation for MSO-Tabu. Figure 1: Number of clusters formed for MSO-Tabu. Figure 3: Average Packet Loss Rate for MSO-Tabu. Figure 2: Average End to End Delay for MSO-Tabu. From Figure 1, it can be observed that the MSO-Tabu has a higher number of clusters formed when compared to the other four metaheuristics. The improvement in MSO-Tabu is approximately 30%, 13%, 8%, 7%, 14%, and 11% as compared to GA for 200, 400, 600, 800, 1000, and 1200 number of nodes respectively. Similarly, as compared to DE, the advantage of MSO-Tabu is 8%, 13%, 4%, 3%, 3%, and 0%.