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Energy-Efficient and Secure Load Balancing Technique for SDN-Enabled Fog Computing

Author

Listed:
  • Jagdeep Singh

    (School of Computer Science and Engineering, Lovely Professional University, Phagwara 144411, India
    Department of Information Technology, Guru Nanak Dev Engineering College, Ludhiana 141006, India)

  • Parminder Singh

    (School of Computer Science and Engineering, Lovely Professional University, Phagwara 144411, India
    School of Computer Science, Mohammed VI Polytechnic University, Ben Guerir 43150, Morocco)

  • El Mehdi Amhoud

    (School of Computer Science, Mohammed VI Polytechnic University, Ben Guerir 43150, Morocco)

  • Mustapha Hedabou

    (School of Computer Science, Mohammed VI Polytechnic University, Ben Guerir 43150, Morocco)

Abstract

The number of client applications on the fog computing layer is increasing due to advancements in the Internet of Things (IoT) paradigm. Fog computing plays a significant role in reducing latency and enhancing resource usage for IoT users’ tasks. Along with its various benefits, fog computing also faces several challenges, including challenges related to resource overloading, security, node placement, scheduling, and energy consumption. In fog computing, load balancing is a difficult challenge due to the increased number of IoT devices and requests, which requires an equal load distribution throughout all available resources. In this study, we proposed a secure and energy-aware fog computing architecture, and we implemented a load-balancing technique to improve the complete utilization of resources with an SDN-enabled fog environment. A deep belief network (DBN)-based intrusion detection method was also implemented as part of the proposed techniques to reduce workload communication delays in the fog layer. The simulation findings showed that the proposed technique provided an efficient method of load balancing in a fog environment, minimizing the average response time, average energy consumption, and communication delay by 15%, 23%, and 10%, respectively, as compared with other existing techniques.

Suggested Citation

  • Jagdeep Singh & Parminder Singh & El Mehdi Amhoud & Mustapha Hedabou, 2022. "Energy-Efficient and Secure Load Balancing Technique for SDN-Enabled Fog Computing," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12951-:d:938373
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    References listed on IDEAS

    as
    1. Shivi Sharma & Hemraj Saini, 2019. "Efficient Solution for Load Balancing in Fog Computing Utilizing Artificial Bee Colony," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 10(4), pages 60-77, October.
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    Cited by:

    1. Mohammed Rizwanullah & Hadeel Alsolai & Mohamed K. Nour & Amira Sayed A. Aziz & Mohamed I. Eldesouki & Amgad Atta Abdelmageed, 2023. "Hybrid Muddy Soil Fish Optimization-Based Energy Aware Routing in IoT-Assisted Wireless Sensor Networks," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    2. Javid Misirli & Emiliano Casalicchio, 2023. "An Analysis of Methods and Metrics for Task Scheduling in Fog Computing," Future Internet, MDPI, vol. 16(1), pages 1-22, December.

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