Please use this identifier to cite or link to this item:
Title: A game theoretic approach to parked vehicle assisted content delivery in vehicular ad hoc networks
Authors: Su, Z
Xu, QC
Hui, YL
Wen, M
Guo, S 
Keywords: Content delivery
Parked vehicle applications
Stackelberg game
Vehicular ad hoc networks
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on vehicular technology, 2017, v. 66, no. 7, p. 6461-6474 How to cite?
Journal: IEEE transactions on vehicular technology 
Abstract: Recently, parked vehicles have been shown to be useful to deliver content in vehicular ad hoc networks, where the parked vehicles can form social communities to share and exchange content with other moving vehicles and road side units (RSUs). However, as it takes resource such as bandwidth and power for parked vehicles and RSUs to deliver content, the incentive scheme with the optimal pricing strategy needs to be studied. Furthermore, because multiple places including RSUs and parked vehicles can deliver content to moving vehicles, the optimal algorithm to determine where to obtain the requested content should also be discussed. Therefore, in this paper, we first propose a framework of content delivery with parked vehicles, where moving vehicles can obtain content from both the RSU and parked vehicles according to the competition and cooperation among them. Then, based on a Stackelberg game, we develop a pricing model where each of the three players, including moving vehicles, RSU, and parked vehicles, can obtain their maximum utilities. Next, a gradient based iteration algorithm is presented to obtain the Stackelberg equilibrium. Finally, the simulation results prove that the proposal can outperform other conventional methods and that each player in the game can obtain its optimal strategy during the content delivery.
ISSN: 0018-9545
EISSN: 1939-9359
DOI: 10.1109/TVT.2016.2630300
Appears in Collections:Journal/Magazine Article

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Apr 3, 2019


Last Week
Last month
Citations as of Jan 19, 2020

Page view(s)

Last Week
Last month
Citations as of Jan 22, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.