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Load Balancing Algorithm on the Immense Scale of Internet of Things in SDN for Smart Cities

Author

Listed:
  • Himanshi Babbar

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India)

  • Shalli Rani

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India)

  • Divya Gupta

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India)

  • Hani Moaiteq Aljahdali

    (Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 37848, Saudi Arabia)

  • Aman Singh

    (Department of Computer Science and Engineering, Lovely Professional University, Punjab 144411, India)

  • Fadi Al-Turjman

    (Research Center for AI and IoT, Artificial Intelligence Engineering Department, Near East University, Mersin 10, Turkey)

Abstract

Since the worldwide Internet of Things (IoT) in smart cities is becoming increasingly popular among consumers and the business community, network traffic management is a crucial issue for optimizing the IoT ’s performance in smart cities. Multiple controllers on a immense scale implement in Software Defined Networks (SDN) in integration with Internet of Things (IoT) as an emerging paradigm enhances the scalability, security, privacy, and flexibility of the centralized control plane for smart city applications. The distributed multiple controller implementation model in SDN-IoT cannot conform to the dramatic developments in network traffic which results in a load disparity between controllers, leading to higher packet drop rate, high response time, and other problems with network performance deterioration. This paper lays the foundation on the multiple distributed controller load balancing (MDCLB) algorithm on an immense-scale SDN-IoT for smart cities. A smart city is a residential street that uses information and communication technology (ICT) and the Internet of Things (IoT) to improve its citizens’ quality of living. Researchers then propose the algorithm on the unbalancing of the load using the multiple controllers based on the parameter CPU Utilization in centralized control plane. The experimental results analysis is performed on the emulator named as mininet and validated the results in ryu controller over dynamic load balancing based on Nash bargaining, efficient switch migration load balancing algorithm, efficiency aware load balancing algorithm, and proposed algorithm (MDCLB) algorithm are executed and analyzed based on the parameter CPU Utilization which ensures that the Utilization of CPU with load balancing is 20% better than the Utilization of CPU without load balancing.

Suggested Citation

  • Himanshi Babbar & Shalli Rani & Divya Gupta & Hani Moaiteq Aljahdali & Aman Singh & Fadi Al-Turjman, 2021. "Load Balancing Algorithm on the Immense Scale of Internet of Things in SDN for Smart Cities," Sustainability, MDPI, vol. 13(17), pages 1-16, August.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:17:p:9587-:d:622067
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    Cited by:

    1. Paweł Dymora & Mirosław Mazurek & Bartosz Sudek, 2021. "Comparative Analysis of Selected Open-Source Solutions for Traffic Balancing in Server Infrastructures Providing WWW Service," Energies, MDPI, vol. 14(22), pages 1-23, November.

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