Section 1Section 1 accommodates the outcomes and dialogue of the proposed and applied strategies for enhancing machine learning with a hybrid optimization technique to predict mobility in VANET. The execution of the challenge (HFSA-VANET) is evaluated and in contrast to that of present technique (CRSM-VANET). Delay, Energy consumption, Drop, Throughput, and Fairness index measured values are computed and in contrast to suggest (HFSA-VANET) and present (CRSM-VANET)29 strategies. In addition, the implementation is finished by way of NS2 stimulation and evaluating the proposed algorithm with these two platforms, alongside with the home windows 10 PRO laptop, whole RAM capability of 10 GB, and processor utilized is Intel® core (7M) i3-6100CPU @ 3.70 GHz processor. The performance metrics are examined within the subsequent part.Performance metrics
Delays happen whereas a packet travels from its supply to its vacation spot.$$delay= frac{size}{bandwidth}.$$
(19)
It is the variety of packets misplaced because of a rogue node (DoS assault).$$Drop=frac{Send ;packet-Received ;packet}{Send ; packet}.$$
(20)
The throughput refers to the quantity of packet information established throughout a vacation spot, which corresponds to the general worth of packets created by the sender node inside a sure time. The components is as follows:$$mathrm{Throughput}hspace{0.17em}=hspace{0.17em}mathrm{obtained ; information ; packet }instances 8/mathrm{information ; packet ; transmission ; interval}.$$
(21)
Results obtained by way of nodeThe performance metrics of the prevailing approach and the proposed technique is in contrast within the desk beneath.The major aim of the performance metrics is to assess the proposed mannequin’s capacity to predict mobility in VANET. According to Table 1, compared to and examined with present methodology, the proposed technique improves machine learning with a hybrid optimization technique to predict mobility in VANET is extra profitable.Table 1 Comparison with present strategy.The delay, vitality consumption, drop, throughput and equity index of the HFSA-VANET and the CRSM-VANET are in contrast beneath.Suggested approach achieves 99 J, 0.093690, 0.897708 for vitality consumption, delay worth, and drop worth in node 20. Furthermore, the brand new approach achieves a Throughput of 31,341, which is greater than the prior strategy. The proposed approach has a equity rating of seven.000000, whereas the present technique has a worth of 8.000000. For vitality consumption, delay worth, and drop worth in node 60, the proposed strategy achieves 47 J, 9.752925, 0.472094. In addition, the brand new technique obtains a Throughput of 31,341, which is bigger than the earlier technique. The prompt technique has a equity rating of three.000000, in contrast to 4.000000 for the current technique. The proposed approach achieves 36 J, 10.902826, 0.376633 for vitality consumption, delay worth, and drop worth in node 60. Furthermore, the prompt approach achieves a Throughput of 28,423 in contrast to 26,749 for the prevailing technique. A equity index worth of two.000000 for the proposed technique vs 4.000000 for the prevailing technique is achieved. For vitality consumption, delay worth, and drop worth in node 80, the prompt strategy achieves 11 J, 15.287826, 0.116375. Furthermore, as in contrast to the earlier strategy, the proposed technique obtains a Throughput of 18,197. The proposed strategy has a equity index of 1.000000, whereas the current technique has a equity rating of two.000000. The Figs. 3, 4, 5, 6 and seven are Delay, Energy Consumption, Drop, Throughput, Fairness Index are obtained by way of node, respectively.Figure 3Delay plot for a proposed and present technique.Figure 4Energy consumption plot for a proposed and present technique.Figure 5Drop plot for proposed and present technique.Figure 6Throughput plot for proposed and present technique.Figure 7Fairness Index plot for the proposed and present technique.Results obtained by way of velocityThe velocity of the proposed approach and the prevailing strategies are in contrast when it comes to delay, vitality consumption, drop, throughput, and equity index. The measured values are demonstrated within the desk beneath. Table 2 exhibits the velocity values of each present and proposed strategies.Table 2 Comparison of the proposed technique to present technique of velocity.The velocity is in contrast to the delay proven in Fig. 8, velocity vs vitality proven in Fig. 9, velocity vs drop proven in Fig. 10, velocity vs throughput proven in Fig. 11, and velocity vs equity index proven in Fig. 12. The velocity is in contrast to the delay, vitality, drop, throughput and equity index, and the graphical illustration is proven beneath.Figure 8Speed vs delay plot for proposed and present technique.Figure 9Speed vs vitality consumption plot for a proposed and present technique.Figure 10Speed vs drop plot for a proposed and present technique.Figure 11Speed vs throughput plot for a proposed and present technique.Figure 12Speed vs equity index plot for a proposed and present technique.In velocity 20, the proposed strategy achieves 1980 J, 1.873793, 19.954160 when it comes to vitality consumption, delay worth, and drop worth. In addition, the brand new technique achieves a Throughput of 150, which is bigger than the earlier technique. The prompt strategy has a equity rating of 6.000000, whereas the current technique likewise has a 6.000000 quantity. The prompt approach achieves 1880 J, 390.117000, 18.883762 for vitality consumption, delay worth, and drop worth in velocity 40. Furthermore, the brand new strategy achieves a Throughput of 35, which is greater than the prevailing technique. The really helpful approach has a equity worth of three.000000, however the present technique has a rating of 4.000000. In velocity 60, the prompt strategy achieves 2220 J, 654.169557, 22.597974 when it comes to vitality consumption, delay, and drop worth. In addition, the proposed technique yields a Throughput of twenty-two vs 16 for the current technique. The prompt approach has a equity index of two.000000, whereas the current technique has a equity index of three.000000. The really helpful technique achieves 880 J, 1223.026093, 9.309993 for vitality consumption, delay worth, and drop worth in velocity 80. Furthermore, the brand new approach achieves a Throughput of 8 and the prevailing approach achieves a throughput of 6. The prompt approach has a equity rating of 0.000000, whereas the present technique has one among 2.000000. The Figs. 8, 9, 10, 11 and 12 are Delay, Energy Consumption, Drop, Throughput, Fairness Index are obtained by way of velocity, respectively. The Section 2 covers the outcomes obtained by way of the MATLAB software program.Section 2This part covers the experimental outcomes obtained by way of MATLAB (VERSION 2020a) for evaluating the performance with the NS2 device. Moreover, we additionally embrace a further parameter to ensure the network lifetime of the proposed mannequin. Therefore, the performance will be confirmed as extremely efficient as the prevailing approach. Here, the performance of the proposed mannequin is evaluated utilizing numerous machine learning approaches equivalent to ANN-HFSA-VANET, SVM-HFSA-VANET, NB-HFSA-VANET, and DT-HFSA-VANET. Thus, the proposed mannequin outcomes will be in contrast and confirmed as simpler than all different present strategies.Initially, the proposed mannequin is evaluated with ANN-HFSA-VANET, SVM-HFSA-VANET, NB-HFSA-VANET, and DT-HFSA-VANET individually. The following Figs. 13, 14, 15 and 16 are displaying the graphical outcomes of ANN, SVM, NB, and DT, respectively. On the opposite hand, to present comparability based on the aggregation of varied machine learning strategies that the proposed technique is evaluating with the only graphical outcomes.Figure 13(a) Dropout ratio, (b) F1 rating, (c) packet supply ratio, (d) Throughput ratio, (e) End to finish delay.Figure 14(a) Dropout ratio, (b) F1 rating, (c) packet supply ratio, (d) Throughput ratio, (e) End to finish delay.Figure 15(a) Drop out ratio, (b) F1 rating, (c) packet supply ratio, (d) Through put ratio, (e) End to finish delay.Figure 16(a) Dropout ratio, (b) F1 rating, (c) packet supply ratio, (d) Through put ratio, (e) End to finish delay.Parameter analysis of ANN-HFSA-VANETThis part offers with the various kinds of parameters of ANN-HFSA-VANET and is analyzed within the graph proven in Fig. 13.The determine talked about above 13 illustrates the assorted performance analysis based on ANN-HFSA-VANET the place (a) exhibits that the proposed approach has obtained minimal dropout, (b) exhibits most F1 rating has been obtained through the use of the proposed approach, (c) illustrates that most packet supply ratio has obtained for the ANN- HFSA-VANET, (d) and (e) present that proposed ANN-HFSA-VANET has generated excessive throughput and minimal delay, respectively.Parameter analysis of Decision Tree (DT)-HFSA-VANETThis part offers with the various kinds of parameters of the Decision Tree and analyzed within the graphs proven in Fig. 14.Figure 14, exhibits the analysis of parameters of DT-HFSA-VANET. (a) exhibits the mimumum drop out ratio of the DT-HFSA-VANET, (b) offers with the utmost rating for F1 rating of DT-HFSA-VANET and its analysis, (c) exhibits packet supply ratio of DT-HFSA-VANET and its values plotted, (d) offers with throughput ratio of DT-HFSA-VANET, (e) offers with finish to finish delay of DT-HFSA-VANET. Standard parameters are analyzed and plotted in a graph and the values elevated on the finish of every graph of the parameter.Parameter analysis of Navie Baves (NB)-HFSA-VANETThis part offers with the various kinds of the parameter of Navie Baves and is analyzed within the graph proven in Fig. 15.In Fig. 15a exhibits that minimal dropout, (b) exhibits that most F1 rating, (c) gives most packet supply ratio, (e) exhibits that minimal delay, respectively for the proposed NB-HFSA-VANET.Parameter analysis of SVMThis part offers with the various kinds of a parameter of SVM and is analyzed within the graph proven in Fig. 16.In Fig. 16a dropout ratio has obtained with minimal ratio, (b) F1 rating has obtained with most rating, (c) packet supply ratio has obtained with most, and (e) exhibits minimal delay.Parameters for analyzing completely different information typesThis part offers with the parameters of various information and their analysis. The values are plotted in a graph.From Fig. 17, the parameter analysis worth of information sorts is examined and plotted in a graph the place (a) denotes network life time obtained for each second, (b) offers with vitality consumption of information packets used per second, (c) offers with by way of put ratio of information sorts and their performance, (d) offers with packet supply ratio of various kinds of information performance.Figure 17(a) Network life time plot, (b) Energy consumption, (c) Throughput ratio, (d) Packet supply ratio.
https://www.nature.com/articles/s41598-022-14255-1
