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Energy-and-delay-aware scheduling and load balancing in vehicular fog networks

Author

Listed:
  • Vivek Sethi

    (Indian Institute of Technology Ropar)

  • Sujata Pal

    (Indian Institute of Technology Ropar)

  • Avani Vyas

    (Indian Institute of Technology Ropar)

  • Shweta Jain

    (Indian Institute of Technology Ropar)

  • Kshirasagar Naik

    (University of Waterloo)

Abstract

Roadside units (RSUs) play an important role in the request fulfillment of vehicles. In rural areas, RSUs are powered by renewable energy sources like solar energy. Hence, the request fulfillment of vehicles must be done in such a way that the energy consumption across RSUs is minimized. The requests are categorized into traditional application (low computation) requests and smart application (high computation) requests. To avoid excessive computation at RSUs, low computation requests are scheduled across RSUs while high computation requests are scheduled across fog servers for processing. In this paper, we propose an online energy-efficient Inter-RSU Scheduling Algorithm (ee-IRSA) and a distributed Ant Colony Optimization-based Load balancing technique (d-ACOL) for optimizing the request fulfillment of traditional and smart application requests, respectively. ee-IRSA ensures minimum and uniform energy consumption across RSUs while d-ACOL ensures minimum queue waiting time of requests across fog servers. In addition, a second-price auction game-based relay vehicle selection technique is proposed which further minimizes the energy consumption of RSUs. Simulation results show that ee-IRSA with relay vehicle selection reduces the energy consumption by $$33\%$$ 33 % , and d-ACOL reduces the queue waiting time by an average of $$48\%$$ 48 % as compared to other load balancing techniques.

Suggested Citation

  • Vivek Sethi & Sujata Pal & Avani Vyas & Shweta Jain & Kshirasagar Naik, 2022. "Energy-and-delay-aware scheduling and load balancing in vehicular fog networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 81(3), pages 373-387, November.
    • Handle: RePEc:spr:telsys:v:81:y:2022:i:3:d:10.1007_s11235-022-00953-8
    DOI: 10.1007/s11235-022-00953-8
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