PERFORMANCE VALIDATION
In this section, a comprehensive experimental validation of the FCDR model takes place under diverse ways. Figure 4.3 depicts the energy consumption analysis of the FCDR method. The figure shows that the FRLDG model has offered maximum energy utilization, but has appeared as an ineffective model. Simultaneously, the MOBFOEER model has attained slightly higher energy consumption over FRLDG model, but it is not lower than FEECIIR model and FCDR models. On the other hand, the FEECIIR model has attained even lower energy consumption over the compared methods. But the presented FCDR model has attained least energy consumption and appeared as an effective model under varying number of IoT nodes.
Figure 4.4 demonstrates the network existence analysis of the FCDR method. The figure portrayed that the FRLDG method has provided lower network duration and is represented as worst method. At the same time, the MOBFOEER approach has accomplished medium network existence than FRLDG method; however, it is not greater than FEECIIR and FCDR methodologies. Besides, the FEECIIR scheme has reached slightly better network duration when compared with earlier technologies. However, the projected FCDR approach has accomplished remarkable network duration and is considered as optimal model under diverse count of IoT nodes.
Figure 4.5 illustrates the PDR analysis of FCDR approach. The figure represented that the FRLDG framework has provided least PDR and is depicted as worst technique. The MOBFO EER scheme has reached minimal PDR over FRLDG model; it is not greater than FEECIIR and FCDR technologies. Then, the FEECIIR framework has accomplished considerable
FIGURE 4.3 Energy consumption analysis of the FCDR model.
FIGURE 4.4 Network lifetime analysis of the FCDR model.
PDR than earlier approaches. Therefore, the proposed FCDR scheme has achieved higher PDR and demonstrated as effectual technology even under different IoT nodes.
Figure 4.6 illustrates the throughput analysis of the FCDR technique. The figure implied that the FRLDG method has provided higher throughput and is considered as an ineffective approach. Concurrently, the MOBFOEER framework has achieved minimum throughput than FRLDG model, but it does not exceed FEECIIR and FCDR approaches. The FEECIIR technique has obtained slightly better throughput over the earlier methods. Hence, the projected FCDR scheme has reached a higher throughput and showcased optimal performance under various numbers of IoT nodes.
FIGURE 4.5 PDR analysis of the FCDR model.
FIGURE 4.6 Throughput analysis of the FCDR model.
Figure 4.7 represents the endtoend delay analysis of the FCDR scheme. The figure portrayed that the FRLDG approach has provided greater endtoend delay and is considered as a worst technology. The MOBFOEER scheme has reached better endtoend delay over FRLDG framework, which does not exceed FEECIIR and FCDR frameworks. The FEECIIR method has minimum endtoend delay than the traditional models. Thus, the projected FCDR approach has reached lower endtoend delay and is shown as a best model under distinct number of IoT nodes.
FIGURE 4.7 Endtoend delay analysis of the FCDR model.
CONCLUSION
This chapter has developed an energyefficient FCDR model for WSNassisted IoT system. The proposed FCDR method operates on three major stages: FCbased node clustering, data collection, and EBLC techniquebased data aggregation. Initially, the IoT sensor nodes perform FC process to select CFls and organize clusters. In the second level, the CMs observe the environment and forward the data to the CH. Finally, in the third level, the CHs perform data aggregation using EBLC technique. The experimental results denoted that the FCDR model has shown superior performance by attaining maximum energy efficiency and network lifetime. In future, the performance of the FCDR can be further improved using routing techniques.
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