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Related Experiment Video

Updated: Sep 22, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

Optimized Distributed Proactive Caching Based on Movement Probability of Vehicles in Content-Centric Vehicular

Seungmin Oh¹, Sungjin Park², Yongje Shin²

¹Department of Computer Science and Engineering, Kongju National University, Cheonan 31080, Chungnam, Korea.

Sensors (Basel, Switzerland)

|May 20, 2022

Summary

This summary is machine-generated.

This study introduces a mobility-aware distributed proactive caching protocol (MDPC) for content-centric vehicular networks (CCVNs). The enhanced MDPC_TO protocol optimizes traffic by intelligently distributing content caching among roadside units (RSUs) based on vehicle movement predictions.

Keywords:

content distribution content-centric networking mobility pre-caching roadside units (RSUs)vehicular networks

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Area of Science:

Computer Science
Networking
Vehicular Technology

Background:

Content-centric vehicular networks (CCVNs) utilize distributed proactive caching for efficient service delivery.
Existing naive caching schemes suffer from high deployment costs, limited RSU capacity, and reduced cache hit ratios.
Need for advanced caching strategies to manage content distribution and reduce data acquisition delays in CCVNs.

Purpose of the Study:

To propose a mobility-aware distributed proactive caching protocol (MDPC) for CCVNs.
To reduce caching redundancy and RSU burden by distributing partial content caching.
To introduce MDPC_TO, an optimized version for minimizing traffic in proactive caching.

Main Methods:

MDPC caches content in roadside units (RSUs) based on predicted vehicle movement patterns.
Utilizes a Markov model to predict vehicle locations and distribute partial content caching among RSUs.
MDPC_TO further optimizes caching by controlling pre-cached content amounts based on mobility probability and RSU backhaul links.

Main Results:

MDPC effectively distributes content caching to mitigate RSU burden and improve cache hit ratios.
MDPC_TO significantly reduces network traffic compared to the original MDPC protocol.
Simulation results validate the efficiency and reduced traffic overhead of MDPC_TO.

Conclusions:

The proposed MDPC protocol enhances proactive caching in CCVNs by considering vehicle mobility.
MDPC_TO offers a superior solution for traffic optimization in content-centric vehicular networks.
The developed protocols address limitations of existing caching schemes, improving performance and efficiency.