Simplified LEACH Protocol with Superior Energy Efficiency for the Internet of Things

Authors

  • Anu Sharma Assistant Professor, College of Computing Science and Information Technology, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh, India
  • Khushboo Sharma Assistant Professor, Department of Electrical Engineeing, Vivekananda Global University, Jaipur, India
  • Vivek Kumar Professor, Department of Information Technology and M.Tech Integrated, Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India
  • Kamalraj R. Professor, Department of Computer Science and IT, Jain(Deemed-to-be University), Bangalore-27, India

Keywords:

Internet of Things (IoT), energy efficiency, LEACH protocol, Alternative Convergent Sunflower Optimization (ACSO)

Abstract

The Internet of Things (IoT) has evolved as a paradigm shifter that allows various intelligent devices to connect and communicate seamlessly. The overall performance and lifespan of the network are, however, seriously hampered by the energy limitations of IoT devices. In order to solve the issue of energy efficiency in IoT networks, this research suggests an asimplifiedLow Energy Adaptive Clustering Hierarchy (LEACH) protocol based on Alternative Convergent Sunflower Optimization (ACSO). The suggested algorithm's diversifying and intensifying mechanisms can find equilibrium with this method's invocation, preventing it from getting trapped in local minimums. By comparing those concepts' approaches to the traditional SO method, CEC2015 evaluations validate the optimization effectiveness. In regards to energy efficiency, network lifespan, and data transmission accuracy, the findings show considerable gains. The findings of this study open the path for future developments in IoT network energy-efficiency approaches, making it possible to realize an IoT ecosystem that is more energy-efficient and durable.

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Published

11.07.2023

How to Cite

Sharma, A. ., Sharma, K. ., Kumar, V. ., & R., K. . (2023). Simplified LEACH Protocol with Superior Energy Efficiency for the Internet of Things. International Journal of Intelligent Systems and Applications in Engineering, 11(8s), 86–92. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3025

Issue

Vol. 11 No. 8s (2023): Advances on Machine Learning and Artificial Intelligence in Computer Technology

Section

Research Article

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