Hierarchical proactive caching for vehicular ad hoc networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Recently, emerging vehicular applications are increasing the demand of vehicles which form significant burdens on network backhaul and represents a cause to the quality of experience (QoE) decay of the vehicular users. Proactive caching is a promising technique to mitigate the load on core networks by caching some of the expected data items. This work proposes a hierarchical proactive caching scheme which jointly considers caching in vehicles and roadside units (RSUs). Minimization of the vehicle communication latency is the main objective of our study. The optimization problem is formulated to find the optimal caching decision at RSUs and vehicles. Numerical results show that proactive caching has a great performance gain compared to the baseline reactive scenario. Moreover, results reveal that caching in vehicles, with small memory cache size, has effective impact on the total network latency.

Original languageEnglish
Title of host publicationNILES 2019 - Novel Intelligent and Leading Emerging Sciences Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages150-153
Number of pages4
ISBN (Electronic)9781728131733
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes
Event2019 Novel Intelligent and Leading Emerging Sciences Conference, NILES 2019 - Giza, Egypt
Duration: Oct 28 2019Oct 30 2019

Publication series

NameNILES 2019 - Novel Intelligent and Leading Emerging Sciences Conference

Conference

Conference2019 Novel Intelligent and Leading Emerging Sciences Conference, NILES 2019
Country/TerritoryEgypt
CityGiza
Period10/28/1910/30/19

Keywords

  • Mobility
  • Proactive caching
  • Vehicular network

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing
  • Industrial and Manufacturing Engineering
  • Control and Optimization
  • Health Informatics

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