A Stackelberg Game-Based Caching Incentive Scheme for Roadside Units in VANETs

Area of Science:

• Intelligent Transportation Systems (ITS)
• Vehicular Ad Hoc Networks (VANETs)
• Wireless Communications

Background:

• Vehicular ad hoc networks (VANETs) are crucial for intelligent transportation systems (ITS), offering safety and infotainment.
• Effective content delivery in VANETs is vital for diverse applications like traffic safety, efficiency, autonomous driving, and entertainment.
• Base stations (BSs) and roadside units (RSUs) require optimal resource management (bandwidth, power) for content delivery.

Purpose of the Study:

• To propose a novel framework for content delivery in VANETs.
• To establish profit models for BSs and RSUs considering their competition.
• To develop an optimal caching incentive scheme for RSUs and a pricing strategy for BSs to maximize profits.

Main Methods:

• A content delivery framework enabling vehicles to select content sources (BS or RSU) based on competition.
• Development of profit models for BSs and RSUs using stochastic geometry and point processes theory.
• Application of a Stackelberg game and backward induction to determine the optimal caching incentive scheme and pricing strategy.

Main Results:

• The proposed framework facilitates content acquisition for vehicles from the most competitive source.
• Profit models accurately represent the economic dynamics between BSs and RSUs.
• The Stackelberg game successfully identifies equilibrium strategies for both BSs and RSUs.

Conclusions:

• BSs can determine optimal pricing strategies to maximize their profits.
• RSUs can implement an optimal caching scheme to achieve maximum profitability.
• The study provides a comprehensive approach to optimizing content delivery economics in VANETs.