Energy-Aware Clustering Using Intelligent Scheme for Heterogeneous Wireless Sensor Networks

Heterogeneous Wireless Sensor Networks (WSNs) involve nodes with varying capabilities, such as different energy levels, sensing ranges, and computational abilities, which enable them to execute different tasks professionally. Clustering techniques play a crucial role in improving energy efficiency and reliability in WSNs. The evolution of cluster based WSNs from homogeneous into heterogeneous techniques allowed the deployment of smart devices capable of performing complex operations in in diverse environments. However, the heterogeneity of nodes necessitates more sophisticated and adaptive algorithms to fully exploit these capabilities. This paper proposes a new protocol, referred to as IT2F-HLEACH, which integrates Interval Type-2 Fuzzy Logic (IT2-FL) to address uncertainties in decision-making processes. The protocol dynamically adjusts the clustering decisions by considering network conditions and the capabilities of individual nodes. Besides, the proposed protocol is designed for two distinct heterogeneous network scenarios: The Two-Level Heterogeneous Scenario and the Three-Level Heterogeneous Scenario. Simulation results obtained using the Castalia simulator with OMNeT++ demonstrate that the recommended protocol significantly prolongs network lifetime, reduces energy consumption, and improves data transmission. The findings indicate that the proposed protocol outperforms the SEP protocol regarding First Node Dead (LND) and Last Node Dead (LND) with initial energy equal to 3J by 321.82% and 36.66 %, respectively. While, the proposed protocol outperforms the EEHC protocol in terms of FND and LND by 235.71% and 71.95%, respectively. This result may be explained by the fact that the lifespan of the IT2F-HLEACH protocol is significantly longer in the two suggested heterogeneous scenarios than SEP and EEHC, resulting in a significant increase in the amount of data transmitted to the sink node.