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Collision-Aware Routing Using Multi-Objective Seagull Optimization Algorithm for WSN-Based IoT.

Preetha Jagannathan1, Sasikumar Gurumoorthy2, Andrzej Stateczny3

  • 1Department of Computer Science and Engineering, Muthayammal Engineering College Autonomous, Rasipuram 637408, Tamil Nadu, India.

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Summary

This study introduces a novel collision-aware routing protocol (CAR-MOSOA) for wireless sensor networks (WSNs) that significantly reduces energy consumption and improves data delivery. The new method enhances network lifetime and performance in Internet of Things (IoT) applications.

Keywords:
Internet of Thingscongestionscalabilityseagull optimization algorithmwireless sensor network

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Area of Science:

  • Computer Science
  • Network Engineering
  • Optimization Algorithms

Background:

  • Wireless Sensor Networks (WSNs) are crucial for the Internet of Things (IoT), but network congestion causes delays and energy waste.
  • Effective routing protocols are essential to manage congestion and enhance WSN performance.
  • Existing protocols often struggle with scalability and efficiency in dynamic network conditions.

Purpose of the Study:

  • To design a collision-aware routing protocol (CAR-MOSOA) optimized for scalable WSNs.
  • To improve network efficiency by addressing congestion and reducing energy consumption.
  • To evaluate the performance of CAR-MOSOA against established routing algorithms.

Main Methods:

  • Developed a novel collision-aware routing protocol (CAR-MOSOA) utilizing a multi-objective seagull optimization algorithm.
  • Implemented a clustering process to select efficient cluster heads for data transfer.
  • Simulated the CAR-MOSOA protocol using the NS-2.34 simulator for performance evaluation.

Main Results:

  • CAR-MOSOA demonstrated superior performance in simulations with 400 nodes.
  • Achieved significantly lower energy consumption (33 J) and end-to-end delay (29 s).
  • Reported a high packet delivery ratio (95%) and extended network lifetime (973 s) compared to FDEAM, EOMR, TSGWO, and CoCoA.

Conclusions:

  • The proposed CAR-MOSOA protocol effectively mitigates congestion in WSNs.
  • CAR-MOSOA offers a scalable and energy-efficient solution for IoT networks.
  • The optimization algorithm significantly enhances key performance metrics, outperforming existing methods.