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An Efficient and Reliable Routing Method for Hybrid Mobile Ad Hoc Networks Using Deep Reinforcement Learning.

Murtadha M A Alkadhmi1, Osman N Uçan1, Muhammad Ilyas1

  • 1ALTINBAŞ University, Engineering and Naturel Science, Mahmutbey, Istanbul, Turkey.

Applied Bionics and Biomechanics
|December 31, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a method to extend the network lifetime of Mobile Ad Hoc Networks (MANETs) for disaster communication. By balancing node load, it enhances survivor rescue chances without compromising performance.

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Area of Science:

  • Computer Science
  • Wireless Communication
  • Network Engineering

Background:

  • Mobile smart devices with wireless communication are increasingly relied upon.
  • Effective communication is crucial for locating and rescuing survivors during disasters.
  • Restoring traditional communication infrastructure post-disaster is often time-consuming.

Purpose of the Study:

  • To propose a method for extending the operational lifetime of Mobile Ad Hoc Networks (MANETs).
  • To ensure continuous communication with the nearest base station (BS) during disaster scenarios.
  • To facilitate rapid, temporary communication links for survivor assistance.

Main Methods:

  • Implementing a load-balancing strategy across network nodes.
  • Prioritizing energy conservation by avoiding the exhaustion of nodes with limited remaining energy.
  • Maintaining stable communication pathways to the base station (BS).

Main Results:

  • Significant improvement in the overall lifetime of the MANET.
  • Comparable Packet Delivery Rate (PDR) to existing methods.
  • Similar route generation time compared to existing methods.

Conclusions:

  • The proposed load-balancing method effectively extends MANET lifetime for disaster response.
  • The approach ensures reliable communication during emergencies while preserving network resources.
  • This methodology offers a viable solution for rapid communication establishment in critical situations.