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eeTMFO/GA: a secure and energy efficient cluster head selection in wireless sensor networks

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Proliferation of technologies in wireless sensor networks is grabbing huge attention across scientific community due to its vast coverage in real life applications. It has emerged as an important technology with lots of potential as it provides useful information to the end users about a target region through real time sensing. Wireless sensor networks due to their characteristics like infrastructure-less deployment, resource restricted nature introduce several issues which may affect the performance of the system. Among these issues, most challenging issues such as energy efficiency, appropriate cluster head selection, secure data delivery and network lifetime enhancement require important concern for enhancement of WSNs which is still herculean task. This paper introduces a secure and energy aware clustering algorithm named energy efficient trusted moth flame optimization and genetic algorithm based clustering algorithm (eeTMFO/GA). Selection of most deserving trustworthy head node (also known as cluster head) is done by using moth flame optimization in clustered WSN framework. In eeTMFO/GA, the fitness function is evaluated on the basis of five important parameters including direct trust metrics such as packet forwarding progress, residual energy of elected node, connected node density, average cluster distance and average delay of transmission. Simulation outcomes have shown significant improvement in energy conservation and network stability period enhancement for eeTMFO/GA in comparison to the existing clustering schemes by 60% in comparison to LEACH protocol, 56.09% when compared to HEED protocol and has shown 42.22% and 16.36% improvement in comparison to ABC and QABC protocols respectively.

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Correspondence to Richa Sharma.

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Sharma, R., Vashisht, V. & Singh, U. eeTMFO/GA: a secure and energy efficient cluster head selection in wireless sensor networks. Telecommun Syst (2020). https://doi.org/10.1007/s11235-020-00654-0

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  • Wireless sensor network
  • Cluster head selection
  • Trust evaluation
  • Moth flame optimization
  • Genetic algorithm