FSRW: fuzzy logic-based whale optimization algorithm for trust-aware routing in IoT-based healthcare

Area of Science:

• Internet of Things (IoT)
• Healthcare Technology
• Network Security

Background:

• The Internet of Things (IoT) offers significant potential in healthcare, particularly for managing chronic diseases and an aging population.
• Existing IoT healthcare systems face challenges related to security and efficient data routing.
• There is a growing need for robust and secure communication protocols in IoT-enabled healthcare.

Purpose of the Study:

• To propose a secure and efficient hierarchical routing protocol for IoT healthcare applications.
• To enhance the trustworthiness and reliability of data transmission in IoT healthcare networks.
• To improve the overall performance of IoT healthcare systems, including network lifespan and energy efficiency.

Main Methods:

• A hierarchical secure routing protocol combining a fuzzy logic system and the Whale Optimization Algorithm (WOA).
• Implementation of a fuzzy trust strategy to assess the trustworthiness of IoT devices.
• Development of a WOA-inspired clustering methodology with a fitness function evaluating potential cluster heads based on centrality, communication range, hop count, energy, and trustworthiness.

Main Results:

• The proposed method demonstrated superior performance compared to existing algorithms.
• Achieved a 47% increase in network lifespan.
• Showcased a 58% improvement in energy usage and a 17.7% enhancement in packet delivery ratio.

Conclusions:

• The novel routing protocol effectively addresses security and efficiency challenges in IoT healthcare.
• The integration of fuzzy logic and WOA significantly optimizes network performance.
• This approach offers a promising solution for secure and reliable data management in the evolving landscape of digital health.