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Efficient content caching for 5G assisted vehicular networks.

Faareh Ahmed1, Badr Alsamani2, Mohammed Alkhathami3

  • 1School of Electrical Engineering & Computer Science (SEECS), National University of Sciences & Technology, Islamabad, Pakistan.

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Summary
This summary is machine-generated.

This study introduces an improved content caching scheme for smart city traffic management. The optimized algorithm enhances content delivery by considering popularity, connectivity, and channel quality, reducing download times.

Keywords:
Content cachingFog nodesSmart cities

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Area of Science:

  • Intelligent Transportation Systems
  • Wireless Communication Networks
  • Edge Computing

Background:

  • Traffic congestion is a significant issue in smart cities, impacting daily commutes.
  • Autonomous transportation systems utilizing 5G-based Cellular Vehicle-to-Everything (C-V2X) offer a solution.
  • Vehicular networks, including Road Side Units (RSUs) and fog computing nodes, enable efficient data exchange.

Purpose of the Study:

  • To address the challenge of limited caching capacity in fog nodes for vehicular networks.
  • To propose an improved content caching scheme for fair content placement between vehicles and content providers.
  • To enhance Quality of Service (QoS) for vehicular infotainment traffic.

Main Methods:

  • Development of a novel content caching algorithm for fog nodes.
  • Modification of the Gale-Shapley technique to optimize caching decisions.
  • Inclusion of content popularity, vehicle connectivity, and communication channel quality as key factors.

Main Results:

  • The proposed scheme successfully caches a higher proportion of popular content.
  • Significant reduction in content downloading time for vehicles.
  • Improved overall quality of service in the vehicular network.

Conclusions:

  • The optimized content caching scheme effectively manages limited fog node resources.
  • The algorithm balances the needs of vehicles and content providers for efficient content distribution.
  • This approach contributes to mitigating traffic congestion and improving the commuter experience in smart cities.