For evaluating performance outcomes depend on the improved Beetle Antenna Search (BAS) algorithm. EDS-BAS, the expected outcome displays that improved BAS algorithm execute extensively better than convex approximation technique. Jiao et al. (2019b) The simulations are carried out on PC by an Intel (R) Core (TM) i5 -7200U, 2.50 GHz CPU, 8GB of RAM and Windows 8. The entire simulation programs are executed inside the NS2 simulator. [2. 3] the simulation parameters for the proposed EDS-BAS algorithm are given below on Table 1
Table 1
Parameters for experimental testing
Total Number of nodes
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100
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Node distribution range
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500mx500m
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Node initial energy
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0.89J
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Node communication radius
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110m
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SINR
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≥10
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Uniform distribution
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U(0,1)
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Noise power
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σ = 1x10-5
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Simulation phase 1: performance comparison of various algorithm:
In this section, several evaluation metrics, such as lag, performance, delivery rate, energy consumption, fairness index, and network life are analyzed. Here, the performance of the BAS algorithm was analyzed and compared to ACO algorithm by changing the number of nodes with constant data rate. In network, the variable channel request is depend on number of nodes provided.
Figure 2 shows the node vs delay for network scenario. The delay value for proposed BAS got 4.596506 values at node 20, 7.189551 values at node 40, 10.323822 values at node 60, 10.906996 values at node 80, and 10.147834 values at node 100.
In the figure, it obviously shown that the delay of the proposed algorithm BAS provides 14.75% lowers than ACO in node 20, delay of the proposed BAS algorithm provides 12.21% lower than ACO at node 40, delay for the proposed BAS algorithm provides 10.48% lower than ACO at node 60, delay for the proposed BAS algorithm provides 10.86% lower than ACO at node 80 and delay of proposed BAS algorithm provides 10.71% lower than ACO at node 100. By this our proposed BAS provides lower delay value compared with ACO.
Figure 3 show the delratio for the number of node in network scenario. The delratio value for proposed BAS got 0.82281 values at node 20, 0.72115 values at node 40, 0.623285 values at node 60, 0.610614 values at node 80 and 0.598908 values at node 100.From the figure, the delratio of the proposed algorithm BAS provides 3.47% higher than ACO in node 20, delratio of the proposed BAS algorithm provides 7.44% higher than ACO at node 40, delratio for the proposed BAS algorithm provides 7.48% higher than ACO at node 60, delratio for the proposed BAS algorithm provides 7.71% higher than ACO at node 80 and delratio of proposed BAS algorithm provides 8.26% higher than ACO at node 100. By this our proposed BAS provides higher delratio compared with ACO.
Figure 4 show the drop for the number of node in network scenario. The drop value for proposed BAS got 2 values at node 20, 8 values at node 16 values at node 60, 12 values at node 80 and 27 values at node 100.From the figure, the drop value of the proposed algorithm BAS provides 60% lowers than ACO in node 20, drop value of the proposed BAS algorithm provides 33.33% lower than ACO at node 40, drop for the proposed BAS algorithm provides 27.27% lower than ACO at node 60, drop for the proposed BAS algorithm provides 52% lower than ACO at node 80 and drop of proposed BAS algorithm provides 15.62% lower than ACO at node 100. By this our proposed BAS provides lower drop value compared with ACO.
Figure 5 show the energy for the number of node in network scenario. The energy value for proposed BAS got 7.578526 values at node 20, 7.845594 values at node 40, 7.887799 values at node 60, 7.603463 values at node 80 and 7.40053 values at node 100.From the figure, the energy of the proposed algorithm BAS provides 2.50% lowers than ACO in node 20, energy value of the proposed BAS algorithm provides 1.62% lower than ACO at node 40, energy for the proposed BAS algorithm provides 0.03% lower than ACO at node 60, energy for the proposed BAS algorithm provides 1.20% lower than ACO at node 80 and energy of proposed BAS algorithm provides 2.05% lower than ACO at node 100. By this our proposed BAS provides lower energy compared with ACO.
Figure 6 show the network lifetime in network scenario. The network life time for proposed BAS got 160 values at node 20, 88 values at node 40, 59 values at node 60, 54 values at node 80 and 52 values at node 100.From the figure, the network lifetime of the proposed algorithm BAS provides 37.93% higher than ACO in node 20, network lifetime of the proposed BAS provides 15.78% higher than ACO at node 40, network lifetime for the proposed BAS algorithm provides 40.47% higher than ACO at node 60, network lifetime for the proposed BAS algorithm provides 38.46% higher than ACO at node 80 and network lifetime of proposed BAS algorithm provides 36.84% higher than ACO at node 100. By this our proposed BAS provides higher network lifetime compared with ACO.
Figure 7 show the overhead for the number of node in network scenario. The overhead value for proposed BAS got 2819 values at node 20, 3548 values at node 40, 4118 values at node 60, 5191 values at node 80 and 6407 values at node 100.From the figure, the overhead of the proposed algorithm BAS provides 42.13% lowers than ACO in node 20, overhead value of the proposed BAS algorithm provides 50% lower than ACO at node 40, overhead for the proposed BAS algorithm provides 44.29% lower than ACO at node 60, overhead for the proposed BAS algorithm provides 44.33% lower than ACO at node 80 and overhead of proposed BAS algorithm provides 44.60% lower than ACO at node 100. By this our proposed BAS provides lower overhead compared with ACO.
Simulation phase 2: performance comparison of various CA techniques:
The comparison analysis of diverse measurements through different number of nodes is shown in following figure. Comparison of delay related to uneven nodes displays at Fig. 9. From the figure, the delay of the proposed method provides 28.60 % lower than EDS-NCS, 42.92% lower than CA at node 20, delay value for proposed EDA-BAS provides 26.01% lower than EDS-NCS, 37.86% lower than CA at node 40, delay value for proposed EDS-BAS provides 21.40% lower than EDS-NCS, 0.31 % lower than CA at node 60, delay value for proposed EDS-BAS provides 21.74% lower than EDS-NCS, 32.10% lower than CA at node 80, delay value for proposed EDS- BAS provides 21.54% lower than EDS-NCS, 33.67% lower than CA at node 100. By this our proposed EDS-BAS provides low value compared with EDS-NCS and CA.
Figure 10 displays the delivery rate of proposed technique with different rates. The delivery rate of proposed technique provides 8.88% more than EDS-NCS, 17.61% more than CA in node 20, delratio for proposed EDA-BAS provides 14.22% higher than EDS-NCS, 27.91% higher than CA at node 40, delratio for proposed EDS-BAS provides 18.89% higher than EDS-NCS, 39.19% higher than CA at node 60, delratio for proposed EDS-BAS provides 19.91% lower than EDS- NCS, 38.98% higher than CA at node 80, delratio for proposed EDS-BAS provides 20.50% higher than EDS-NCS, 42% lower than CA at node 100. By this our proposed EDS-BAS provides high value compared with EDS-NCS and CA.
Figure 11shows the drop of the proposed technique with varying rates. From figure, the drop of proposed technique provides 80% lower than EDS-NCS, 60% lower than CA at node 20, drop value for proposed EDA-BAS provides 69.23% lower than EDS-NCS, 33.33% lower than CA at node 40, drop value for proposed EDS-BAS provides 42.85% lower than EDS-NCS, 6.66% lower than CA at node 60, drop value for proposed EDS-BAS provides 81.81% lower than EDS-NCS, 33.33% lower than CA at node 80, drop value for proposed EDS-BAS provides 61.42% lower than EDS-NCS, 47.05% lower than CA at node 100. By this our proposed EDS-BAS provides low value compared with EDS-NCS and CA.
From the Fig. 12, the energy consumption of the proposed method provides 23.87% lower than EDS-NCS, 42.31% lower than CA at node 20, energy consumption for proposed EDA-BAS provides 22.32% lower than EDS-NCS, 40.75% lower than CA at node 40, energy consumption for proposed EDS-BAS provides 21.76% lower than EDS-NCS, 40.45% lower than CA at node 60, energy consumption for proposed EDS-BAS provides 22.57% lower than EDS-NCS, 41.51% lower than CA at node 80, energy consumption for proposed EDS-BAS provides 23.46% lower than EDS-NCS, 41.82% lower than CA at node 100. By this our proposed EDS-BAS provides low value compared with EDS-NCS and CA.
Figure 13shows the network lifetime of the proposed technique with varying rates. The network lifetime of proposed technique provides 92.77% greater than EDS-NCS, 201.88% higher than CA at node 20, network lifetime for proposed EDA-BAS provides 91.30% higher than EDS- NCS, 203.44% higher than CA at node 40, network lifetime for proposed EDS-BAS provides 96.66% higher than EDS-NCS, 210.52% higher than CA at node 60, network lifetime for proposed EDS-BAS provides 92..85% lower than EDS-NCS, 200% higher than CA at node 80, network lifetime for proposed EDS-BAS provides 92.59% higher than EDS-NCS, 205.88% lower than CA at node 100. By this our proposed EDS-BAS provides high value compared with EDS-NCS and CA.
From the Fig. 14, the overhead of the proposed method provides 31.19% lower than EDS- NCS, 15.14% lower than CA at node 20, overhead for proposed EDA-BAS provides 34.33% lower than EDS-NCS, 21.86% lower than CA at node 40, overhead for proposed EDS-BAS provides 37% lower than EDS-NCS, 28.37% lower than CA at node 60, overhead for proposed EDS-BAS provides 37.45% lower than EDS-NCS, 28.17% lower than CA at node 80, overhead for proposed EDS-BAS provides 37.78% lower than EDS-NCS, 29.68% lower than CA at node 100. By this our proposed EDS-BAS provides low value compared with EDS-NCS and CA.
Figure 15 demonstrates the throughput of improved BAS technique with varying rates. The throughput of the proposed technique provides 49.83% superior than EDS-NCS, 99..61% higher than CA at node 20, throughput for proposed EDA-BAS provides 50.04% higher than EDS-NCS, 99.92% higher than CA at node 40, throughput for proposed EDS-BAS provides 49.81% higher than EDS-NCS, 99.37% higher than CA at node 60, throughput for proposed EDS-BAS provides 50.02% lower than EDS-NCS, 99.68% higher than CA at node 80, throughput for proposed EDS- BAS provides 49.96% higher than EDS-NCS, 99.71% lower than CA at node 100. By this our proposed EDS-BAS provides high value compared with EDS-NCS and CA.