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Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol

Author

Listed:
  • Salil Bharany

    (Department of Computer Engineering & Technology, Guru Nanak Dev University, Punjab 143005, India)

  • Sandeep Sharma

    (Department of Computer Engineering & Technology, Guru Nanak Dev University, Punjab 143005, India)

  • Sumit Badotra

    (Department of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab 144402, India)

  • Osamah Ibrahim Khalaf

    (Al-Nahrain Nano-Renewable Energy Research Center, Al-Nahrain University, Baghdad 10072, Iraq)

  • Youseef Alotaibi

    (Department of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah 21955, Saudi Arabia)

  • Saleh Alghamdi

    (Department of Information Technology, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia)

  • Fawaz Alassery

    (Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia)

Abstract

A Flying Ad-hoc network constitutes many sensor nodes with limited processing speed and storage capacity as they institute a minor battery-driven device with a limited quantity of energy. One of the primary roles of the sensor node is to store and transmit the collected information to the base station (BS). Thus, the life span of the network is the main criterion for the efficient design of the FANETS Network, as sensor nodes always have limited resources. In this paper, we present a methodology of an energy-efficient clustering algorithm for collecting and transmitting data based on the Optimized Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. The selection of CH is grounded on the new optimized threshold function. In contrast, LEACH is a hierarchical routing protocol that randomly selects cluster head nodes in a loop and results in an increased cluster headcount, but also causes more rapid power consumption. Thus, we have to circumvent these limitations by improving the LEACH Protocol. Our proposed algorithm diminishes the energy usage for data transmission in the routing protocol, and the network’s lifetime is enhanced as it also maximizes the residual energy of nodes. The experimental results performed on MATLAB yield better performance than the existing LEACH and Centralized Low-Energy Adaptive Clustering Hierarchy Protocol in terms of energy efficiency per unit node and the packet delivery ratio with less energy utilization. In addition, the First Node Death (FND) is also meliorated when compared to the LEACH and LEACH-C protocols.

Suggested Citation

  • Salil Bharany & Sandeep Sharma & Sumit Badotra & Osamah Ibrahim Khalaf & Youseef Alotaibi & Saleh Alghamdi & Fawaz Alassery, 2021. "Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol," Energies, MDPI, vol. 14(19), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6016-:d:640414
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    References listed on IDEAS

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    1. Salvina Gagliano & Fabiana Cairone & Angelo Amenta & Maide Bucolo, 2019. "A Real Time Feed Forward Control of Slug Flow in Microchannels †," Energies, MDPI, vol. 12(13), pages 1-11, July.
    2. Guang Li & Fangfang Liu & Ashutosh Sharma & Osamah Ibrahim Khalaf & Youseef Alotaibi & Abdulmajeed Alsufyani & Saleh Alghamdi, 2021. "Research on the Natural Language Recognition Method Based on Cluster Analysis Using Neural Network," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-13, May.
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    Cited by:

    1. Mohammed Shuaib & Sumit Badotra & Muhammad Irfan Khalid & Abeer D. Algarni & Syed Sajid Ullah & Sami Bourouis & Jawaid Iqbal & Salil Bharany & Lokesh Gundaboina, 2022. "A Novel Optimization for GPU Mining Using Overclocking and Undervolting," Sustainability, MDPI, vol. 14(14), pages 1-15, July.
    2. Mohammed I. Alghamdi, 2022. "Optimization of Load Balancing and Task Scheduling in Cloud Computing Environments Using Artificial Neural Networks-Based Binary Particle Swarm Optimization (BPSO)," Sustainability, MDPI, vol. 14(19), pages 1-20, September.
    3. Mudassir Khan & A. Ilavendhan & C. Nelson Kennedy Babu & Vishal Jain & S. B. Goyal & Chaman Verma & Calin Ovidiu Safirescu & Traian Candin Mihaltan, 2022. "Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN," Energies, MDPI, vol. 15(13), pages 1-14, June.
    4. Edeh Michael Onyema & M. Anand Kumar & Sundaravadivazhagn Balasubaramanian & Salil Bharany & Ateeq Ur Rehman & Elsayed Tag Eldin & Muhammad Shafiq, 2022. "A Security Policy Protocol for Detection and Prevention of Internet Control Message Protocol Attacks in Software Defined Networks," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    5. Satheeshkumar Palanisamy & Balakumaran Thangaraju & Osamah Ibrahim Khalaf & Youseef Alotaibi & Saleh Alghamdi & Fawaz Alassery, 2021. "A Novel Approach of Design and Analysis of a Hexagonal Fractal Antenna Array (HFAA) for Next-Generation Wireless Communication," Energies, MDPI, vol. 14(19), pages 1-18, September.
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    7. Salil Bharany & Sandeep Sharma & Surbhi Bhatia & Mohammad Khalid Imam Rahmani & Mohammed Shuaib & Saima Anwar Lashari, 2022. "Energy Efficient Clustering Protocol for FANETS Using Moth Flame Optimization," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    8. Manreet Sohal & Salil Bharany & Sandeep Sharma & Mashael S. Maashi & Mohammed Aljebreen, 2022. "A Hybrid Multi-Cloud Framework Using the IBBE Key Management System for Securing Data Storage," Sustainability, MDPI, vol. 14(20), pages 1-24, October.
    9. Hemavathi & Sreenatha Reddy Akhila & Youseef Alotaibi & Osamah Ibrahim Khalaf & Saleh Alghamdi, 2022. "Authentication and Resource Allocation Strategies during Handoff for 5G IoVs Using Deep Learning," Energies, MDPI, vol. 15(6), pages 1-27, March.
    10. Akashdeep Bhardwaj & Keshav Kaushik & Mashael S. Maashi & Mohammed Aljebreen & Salil Bharany, 2022. "Alternate Data Stream Attack Framework to Perform Stealth Attacks on Active Directory Hosts," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    11. Amit Sundas & Sumit Badotra & Salil Bharany & Ahmad Almogren & Elsayed M. Tag-ElDin & Ateeq Ur Rehman, 2022. "HealthGuard: An Intelligent Healthcare System Security Framework Based on Machine Learning," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
    12. Shailendra Pratap Singh & Youseef Alotaibi & Gyanendra Kumar & Sur Singh Rawat, 2022. "Intelligent Adaptive Optimisation Method for Enhancement of Information Security in IoT-Enabled Environments," Sustainability, MDPI, vol. 14(20), pages 1-23, October.
    13. Kuruva Lakshmanna & Neelakandan Subramani & Youseef Alotaibi & Saleh Alghamdi & Osamah Ibrahim Khalafand & Ashok Kumar Nanda, 2022. "Improved Metaheuristic-Driven Energy-Aware Cluster-Based Routing Scheme for IoT-Assisted Wireless Sensor Networks," Sustainability, MDPI, vol. 14(13), pages 1-19, June.
    14. Salil Bharany & Sandeep Sharma & Osamah Ibrahim Khalaf & Ghaida Muttashar Abdulsahib & Abeer S. Al Humaimeedy & Theyazn H. H. Aldhyani & Mashael Maashi & Hasan Alkahtani, 2022. "A Systematic Survey on Energy-Efficient Techniques in Sustainable Cloud Computing," Sustainability, MDPI, vol. 14(10), pages 1-89, May.
    15. Supreet Kaur & Sandeep Sharma & Ateeq Ur Rehman & Elsayed Tag Eldin & Nivin A. Ghamry & Muhammad Shafiq & Salil Bharany, 2022. "Predicting Infection Positivity, Risk Estimation, and Disease Prognosis in Dengue Infected Patients by ML Expert System," Sustainability, MDPI, vol. 14(20), pages 1-20, October.

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