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A Stackelberg Game-Based Caching Incentive Scheme for Roadside Units in VANETs.
Wang, Yang; Lin, Yuankun; Chen, Lingyu; Shi, Jianghong.
Afiliação
  • Wang Y; School of Informatics, Xiamen University, Xiamen 361005, China.
  • Lin Y; School of Informatics, Xiamen University, Xiamen 361005, China.
  • Chen L; School of Informatics, Xiamen University, Xiamen 361005, China.
  • Shi J; School of Informatics, Xiamen University, Xiamen 361005, China.
Sensors (Basel) ; 20(22)2020 Nov 19.
Article em En | MEDLINE | ID: mdl-33228052
ABSTRACT
As a key technology of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs) have been promising to provide safety and infotainment for drivers and passengers. To support different applications about traffic safety, traffic efficiency, autonomous driving and entertainment, it is important to investigate how to effectively deliver content in VANETs. Since it takes resources such as bandwidth and power for base stations (BSs) or roadside units (RSUs) to deliver content, the optimal pricing strategy for BSs and the optimal caching incentive scheme for RSUs need to be studied. In this paper, a framework of content delivery is proposed first, where each moving vehicle can obtain small-volume content files from either the nearest BS or the nearest RSU according to the competition among them. Then, the profit models for both BSs and RSUs are established based on stochastic geometry and point processes theory. Next, a caching incentive scheme for RSUs based on Stackelberg game is proposed, where both competition sides (i.e., BSs and RSUs) can maximize their own profits. Besides, a backward introduction method is introduced to solve the Stackelberg equilibrium. Finally, the simulation results demonstrate that BSs can obtain their own optimal pricing strategy for maximizing the profit as well as RSUs can obtain the optimal caching scheme with the maximum profit during the content delivery.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article