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A review on recent studies utilizing artificial intelligence methods for solving routing challenges in wireless

Walid Osamy1,2, Ahmed M Khedr3,4, Ahmed Salim4,5

  • 1Computer Science Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt.

Peerj. Computer Science
|November 25, 2022
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Summary

This survey explores Artificial Intelligence (AI) methods for enhancing Wireless Sensor Networks (WSNs), focusing on routing challenges. It analyzes AI applications in WSNs from 2010-2020 to guide future research.

Keywords:
Artificial intelligenceChallengesData aggregationData collectionData disseminationInternet of ThingsRoutingWireless Sensor Networks

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Artificial Intelligence

Background:

  • Wireless Sensor Networks (WSNs) are crucial for smart environments, smart cities, manufacturing, and the Internet of Things (IoT).
  • The routing challenge in WSNs significantly impacts network performance and efficiency.
  • AI methods offer potential solutions for optimizing WSN operations.

Purpose of the Study:

  • To review and analyze research trends in Artificial Intelligence (AI) methods applied to Wireless Sensor Networks (WSNs).
  • To investigate the application of AI in addressing the critical routing challenge within WSNs.
  • To provide a comprehensive overview of AI-driven WSN routing solutions from 2010 to 2020.

Main Methods:

  • Systematic literature review and analysis of AI techniques used in WSNs.
  • Categorization and evaluation of AI methods specifically for WSN routing.
  • Comparative analysis of different AI approaches for WSN routing challenges.

Main Results:

  • Identified key AI methods utilized for WSN routing challenges between 2010 and 2020.
  • Highlighted the effectiveness of various AI techniques in meeting specific WSN objectives.
  • Provided an evaluation and comparison of AI methods for WSN routing.

Conclusions:

  • AI methods show significant promise in enhancing WSN performance, particularly in routing.
  • The study guides researchers in selecting appropriate AI techniques for WSN routing problems.
  • Identified open research issues and future directions for AI in WSNs.