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Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication.

Someah Alangari1, Marwa Obayya2, Abdulbaset Gaddah3

  • 1Department of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra 11961, Saudi Arabia.

Sensors (Basel, Switzerland)
|November 11, 2022
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Summary
This summary is machine-generated.

A new routing protocol, Wavelet Mutation with Aquila Optimization-based Energy-Aware Routing (WMAO-EAR), enhances wireless sensor network (WSN) performance. This energy-aware approach optimizes data transmission for improved efficiency and scalability in WSNs.

Keywords:
Aquila optimizerrouting protocolwavelet mutationwireless communicationwireless sensor networks

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Area of Science:

  • Computer Science
  • Network Engineering
  • Optimization Algorithms

Background:

  • Wireless Sensor Networks (WSNs) are crucial for diverse applications like environmental monitoring and smart automation.
  • Efficient routing is vital in WSNs for data transmission between sensor nodes (SNs) and base stations (BS).
  • Existing routing protocols face challenges in scalability, energy consumption, security, and adaptability to network changes.

Purpose of the Study:

  • To introduce an energy-aware routing protocol for Wireless Sensor Networks (WSNs).
  • To enhance routing efficiency by integrating wavelet mutation with Aquila Optimization (AO).
  • To address key routing complexities including delay, energy, distance, and security.

Main Methods:

  • Developed the Wavelet Mutation with Aquila Optimization-based Energy-Aware Routing (WMAO-EAR) protocol.
  • Integrated wavelet mutation into the Aquila Optimization (AO) algorithm for enhanced exploration and exploitation.
  • Designed a fitness function incorporating constraints such as delay, energy, distance, and security.

Main Results:

  • The WMAO-EAR protocol demonstrated superior performance in wireless sensor network simulations.
  • The integration of wavelet mutation improved the optimization process within the Aquila algorithm.
  • Experimental results confirmed the effectiveness of WMAO-EAR over existing routing methods.

Conclusions:

  • The WMAO-EAR protocol offers a significant advancement in energy-aware routing for WSNs.
  • The proposed method effectively balances multiple routing constraints for optimal network operation.
  • WMAO-EAR provides a scalable and efficient solution for modern wireless communication challenges.