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Mobility-Aware Proactive Edge Caching Optimization Scheme in Information-Centric IoV Networks.

Salahadin Seid Musa1, Marco Zennaro2, Mulugeta Libsie1

  • 1Department of Computer Science, Addis Ababa University, Addis Ababa P.O. Box 1176, Ethiopia.

Sensors (Basel, Switzerland)
|February 26, 2022
PubMed
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This study introduces a mobility-aware proactive caching scheme for vehicular networks. The proposed Information-Centric Network approach significantly reduces latency and improves cache hits for delay-sensitive services.

Area of Science:

  • Computer Science
  • Network Engineering
  • Information Systems

Background:

  • Edge caching is crucial for Internet of Vehicle (IoV) networks, reducing backhaul burden.
  • Limited edge device resources pose challenges for caching all content and meeting user demands.
  • Existing solutions struggle with the dynamic nature of vehicular environments.

Purpose of the Study:

  • To design a mobility-aware proactive caching scheme for Information-Centric Networks (ICN) in IoV.
  • To enhance performance for delay-sensitive services by optimizing edge caching decisions.
  • To address limitations of current edge caching strategies in dynamic vehicular settings.

Main Methods:

  • Modeling vehicle and Roadside Unit (RSU) interactions using a Markov process.
Keywords:
QoSedge cachinginformation centric networksinternet of vehiclesmobilityproactive content cachingroadside unitvehicular caching

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  • Implementing a mobility-aware proactive edge caching strategy.
  • Utilizing an Information-Centric Network (ICN) architecture.

    • Main Results:

    • The proposed scheme reduces latency by 20-25% compared to related caching schemes.
    • Cache hit rates are improved by 15-23% with the new approach.
    • Demonstrated effectiveness in maximizing network performance and minimizing transmission delay.

    Conclusions:

    • The mobility-aware proactive caching scheme offers significant improvements for IoV networks.
    • ICN architecture combined with proactive caching effectively handles vehicular mobility and data demands.
    • The approach provides a robust solution for delay-sensitive services in IoV environments.