Energy efficient trust ware routing protocol for improving heterogenous wireless sensor network for maximizing lifetime using swarm intelligence optimization algorithm
DOI:
https://doi.org/10.22399/ijcesen.2478Keywords:
WSN, energy efficiency , network lifetime , EETWRP, swarm intelligence, TIBRAbstract
In the realm of wireless sensor networks (WSNs), the increasing demand for energy efficiency and prolonged network lifetime is paramount, particularly in heterogeneous environments where sensor nodes exhibit varying capabilities and energy constraints. Preliminary model has so many routings congestion and energy consumption degrade he throughput latency to downgrade the network life time. This paper presents an innovative Energy Efficient Trust Ware Routing Protocol (EETWRP) designed to enhance the operational longevity of heterogeneous WSNs by leveraging swarm intelligence optimization algorithms. The proposed protocol addresses critical challenges in energy consumption and trust management, which are essential for maintaining network integrity and performance. EETWRP employs a multi-layered approach that integrates trust evaluation mechanisms with energy-aware routing strategies. Based On Traffic Intensive Behaviour Rate (TIBR) And Cross Layer Multicasting Energy Aware-Route Selection (CLM-EARS). By utilizing swarm intelligence, specifically inspired by the collective behaviors of social organisms, the protocol dynamically adjusts routing paths based on real-time energy availability and trustworthiness of sensor nodes. This adaptability not only optimizes energy utilization but also mitigates the risks associated with malicious activities and unreliable data transmission, which are prevalent in WSNs. Simulation results demonstrate that EETWRP significantly outperforms traditional routing protocols in terms of network lifetime, energy consumption, and data accuracy. The findings indicate a marked improvement in the overall efficiency of data transmission, with a reduction in energy expenditure and an increase in the reliability of the network. Furthermore, the protocol's ability to adapt to changing network conditions and node behaviors underscores its potential applicability in various domains, including environmental monitoring, smart cities, and industrial automation.
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