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Related Experiment Videos

Elephant herd clustering with adaptive optimization for secure routing protocol in IoT network.

Kranthi Alluri1, Gopikrishnan Sundaram2

  • 1School of Computer Science and Engineering, VIT-AP University, Amaravathi, Guntur, 522241, Andhra Pradesh, India.

Scientific Reports
|May 12, 2026
PubMed
Summary

This study introduces a new protocol for Internet of Things (IoT) networks that enhances security and energy efficiency. The novel approach optimizes cluster formation and routing in Wireless Sensor Networks (WSNs) for better performance.

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Area of Science:

  • Computer Science
  • Network Security
  • Artificial Intelligence

Background:

  • The Internet of Things (IoT) involves numerous interconnected devices, creating challenges in network management and security.
  • Wireless Sensor Networks (WSNs) are crucial components of IoT, requiring efficient energy consumption and robust security.

Purpose of the Study:

  • To propose a novel protocol that balances energy efficiency and security in IoT networks.
  • To enhance data dissemination security and minimize energy consumption in WSNs.

Main Methods:

  • Integration of Elephant Herding Optimization (EHO) and Adaptive Humpback Whale Optimization (AHWOA) with fuzzy logic.
  • Implementation of lightweight, trust-based authentication mechanisms.
  • Optimized cluster formation and routing strategies for efficient data aggregation and resource allocation.

Main Results:

  • Significant improvements in energy utilization, network lifetime, and throughput.
  • Reduced computational and communication costs, with faster signing and verification times.
  • Enhanced packet delivery ratio and minimized network delay compared to existing protocols.

Conclusions:

  • The proposed EHC-FD protocol demonstrates robust performance in diverse IoT network scenarios.
  • It offers a promising solution for addressing the energy-security trade-off in IoT networks.
  • The integration of advanced optimization algorithms and fuzzy logic proves effective for WSN management.