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EGCIR: Energy-Aware Graph Clustering and Intelligent Routing Using Supervised System in Wireless Sensor Networks

Author

Listed:
  • Tanzila Saba

    (Artificial Intelligence & Data Analytics Lab (AIDA), College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh 11586, Saudi Arabia)

  • Khalid Haseeb

    (Department of Computer Science, Islamia College University, Peshawar 25000, Pakistan)

  • Ikram Ud Din

    (Department of Information Technology, The University of Haripur, Haripur 22620, Pakistan)

  • Ahmad Almogren

    (Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia)

  • Ayman Altameem

    (Department of Natural and Engineering Sciences, College of Applied Studies and Community Services, King Saud University, Riyadh 11543, Saudi Arabia)

  • Suliman Mohamed Fati

    (Artificial Intelligence & Data Analytics Lab (AIDA), College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh 11586, Saudi Arabia)

Abstract

In recent times, the field of wireless sensor networks (WSNs) has attained a growing popularity in observing the environment due to its dynamic factors. Sensor data are gathered and forwarded to the base station (BS) through a wireless transmission medium. The data from the BS is further distributed to end-users using the Internet for their post analysis and operations. However, all sensors except the BS have limited constraints in terms of memory, energy and computational resources that degrade the network performance concerning the network lifetime and trustworthy routing. Therefore, improving energy efficiency with reliable and secure transmissions is a valuable debate among researchers for critical applications based on low-powered sensor nodes. In addition, security plays a significant cause to achieve responsible communications among sensors due to their unfixed and variable infrastructures. Keeping in view the above-mentioned issues, this paper presents an energy-aware graph clustering and intelligent routing (EGCIR) using a supervised system for WSNs to balance the energy consumption and load distribution. Moreover, a secure and efficient key distribution in a hierarchy-based mechanism is adopted by the proposed solution to improve the network efficacy in terms of routes and links integrity. The experimental results demonstrated that the EGCIR protocol enhances the network throughput by an average of 14%, packet drop ratio by an average of 50%, energy consumption by an average of 13%, data latency by an average of 30.2% and data breaches by an average of 37.5% than other state-of-the-art protocols.

Suggested Citation

  • Tanzila Saba & Khalid Haseeb & Ikram Ud Din & Ahmad Almogren & Ayman Altameem & Suliman Mohamed Fati, 2020. "EGCIR: Energy-Aware Graph Clustering and Intelligent Routing Using Supervised System in Wireless Sensor Networks," Energies, MDPI, vol. 13(16), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4072-:d:395424
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    References listed on IDEAS

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    1. Ubaid Ullah & Anwar Khan & Mahdi Zareei & Ihsan Ali & Hasan Ali Khattak & Ikram Ud Din, 2019. "Energy-Effective Cooperative and Reliable Delivery Routing Protocols for Underwater Wireless Sensor Networks," Energies, MDPI, vol. 12(13), pages 1-22, July.
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    Cited by:

    1. Naveed Islam & Khalid Haseeb & Muhammad Ali & Gwanggil Jeon, 2022. "Secured Protocol with Collaborative IoT-Enabled Sustainable Communication Using Artificial Intelligence Technique," Sustainability, MDPI, vol. 14(14), pages 1-12, July.
    2. Mohamed Elhoseny & Khalid Haseeb & Asghar Ali Shah & Irshad Ahmad & Zahoor Jan & Mohammed. I. Alghamdi, 2021. "IoT Solution for AI-Enabled PRIVACY-PREServing with Big Data Transferring: An Application for Healthcare Using Blockchain," Energies, MDPI, vol. 14(17), pages 1-17, August.
    3. Naveed Islam & Majid Altamimi & Khalid Haseeb & Mohammad Siraj, 2021. "Secure and Sustainable Predictive Framework for IoT-Based Multimedia Services Using Machine Learning," Sustainability, MDPI, vol. 13(23), pages 1-15, November.
    4. Piotr Arabas & Andrzej Sikora & Wojciech Szynkiewicz, 2021. "Energy-Aware Activity Control for Wireless Sensing Infrastructure Using Periodic Communication and Mixed-Integer Programming," Energies, MDPI, vol. 14(16), pages 1-17, August.

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