With the advent of low-cost circuitry, sensor and communication technologies, it is feasible to sense and communicate the condition of surroundings to end user. The wireless networks of these circuits, called Wireless Sensor Network (WSN) that are utilized in a multitude of applications such as in hospitals, smart industries, environmental sensing and military protection. WSN's main issue is efficient data sharing between various sensors and efficient communication with sink. However, in the real-world sensors have restricted range of communication and resources, which in turn imposes constraints for successful coordination in the design of the communication strategy. Investigating the trust level of a node is also a significant aspect of WSNs using which two sensor nodes can communicate since an untrustworthy node has adverse effect on the reliability and quality of data. The biggest challenge in this domain is to devise a suitable communication system that helps sensors to achieve their target with minimal energy loss and high confidence level transmission of the full exploration data. Clustering is an effective way to extend the network performance parameters. In order to address the restrictions in these protocols such as cluster head (CH) lifetime, cluster quality etc.; an enhanced routing protocol with optimum CH selection algorithm and trust management are required to design an efficient WSN framework. A hybrid sooty tern naked mole rat algorithm (STNMRA) is developed to mitigate the effect of local stagnation problem in classical naked mole rat algorithm (NMRA). In order to evaluate the effectiveness of proposed STNMRA, highly challenging CEC 2019 numerical test problems are taken into consideration and statistical test validates that STNMRA provides better results with respect to competitive algorithms. STNMRA based clustering protocol using a Fuzzy Type-2 logic is proposed in this paper to enhance the trust level and thus the network lifetime. The proposed clustering protocol outperforms state-of-the-art techniques in terms of the efficient removal of malicious nodes together with improved network lifespan and reduced energy consumption.The source code for the proposed algorithms is available at: https://github.com/mittalnitinsvsu/STNMRA.
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