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AI Assisted Energy Optimized Sustainable Model for Secured Routing in Mobile Wireless Sensor Network

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Abstract

With the rapid development of cognitive computing and the Internet of Things (IoT), sensing systems have produced a wide range of real-time communication applications. They use 5G/6G-enabled technologies to connect to the outside world to collect data and process different end-user requests. Wireless systems and artificial intelligence (AI) have led to significant development in the optimization process of network communication. Due to various constraints of wireless systems, many solutions have been presented to cope with routing and connectivity concerns. However, topology awareness and attaining management of quality of services are still demanding research challenges for sustainable development. This study proposes an AI-assisted routing model for mobile wireless sensor networks (MWSN) to optimize energy and detect communication link failures. Moreover, the proposed intelligent security approach increases the trustworthiness of the constraint devices on unpredictable routes. Firstly, it explores a genetic algorithm, a metaheuristic optimization technique to determine the feasible solutions, and based on independent metrics it generates an optimal set of routes. In the proposed model, the genetic algorithm provides a fault-tolerant solution for dynamic environments, specifically under unpredictable conditions. Second, new routes are established using dynamic decisions that satisfy the energy considerations. In the end, the proposed model performs regular auditing to detect malicious devices based on unexpected behavior. The proposed model is tested and it outperforms IMD-EACBR and AGRIC in terms of realistic performance metrics.

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Acknowledgements

This research was supported by the Artificial Intelligence & Data Analytics (AIDA) lab CCIS Prince Sultan University, Riyadh, Saudi Arabia. Authors are thanked for their support.

The author, Fahad F. Alruwaili, would like to thank the Deanship of Scientific Research at Shaqra University for supporting this research.

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Authors and Affiliations

  1. Artificial Intelligence & Data Analytics (AIDA) Lab, CCIS Prince Sultan University, Riyadh, 12435, Saudi Arabia

    Khalid Haseeb, Abrar Wafa & Amjad R. Khan

  2. Department of Computer & Network Engineering, College of Computing & Information Technology, Shaqra University, Shaqra, Saudi Arabia

    Fahad F. Alruwaili

  3. Department of Computer Science, Islamia College Peshawar, Peshawar, 25120, Pakistan

    Atif Khan

  4. Department of Industrial Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al Kharj, 11942, Kingdom of Saudi Arabia

    Teg Alam

  5. Azad Institute of Engineering and Technology, Azad puram, Chandrawal via Bangla Bazar & Bijnour, Near CRPF Camp, Lucknow, 226002, India

    Teg Alam

Authors
  1. Khalid Haseeb
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  2. Fahad F. Alruwaili
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  3. Atif Khan
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  4. Teg Alam
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  5. Abrar Wafa
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  6. Amjad R. Khan
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Contributions

KH contributed in Conceptualization, Data curation, Methodology writing; FA involved in Methodology, Resources, review & editing; AK contributed in Data curation, analysis, Resources, Writing – original draft; TA involved in analysis, review & editing; AW involved in Conceptualization, Data curation, software review; AK involved in Conceptualization, Methodology, Software and review. All authors had approved the final version.

Corresponding author

Correspondence to Fahad F. Alruwaili.

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Haseeb, K., Alruwaili, F.F., Khan, A. et al. AI Assisted Energy Optimized Sustainable Model for Secured Routing in Mobile Wireless Sensor Network. Mobile Netw Appl (2024). https://doi.org/10.1007/s11036-024-02327-7

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