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Joint Sponsored and Edge Caching Content Service Market: A Game-Theoretic Approach
Author(s) -
Zehui Xiong,
Shaohan Feng,
Dusit Niyato,
Ping Wang,
Amir Leshem,
Zhu Han
Publication year - 2019
Publication title -
ieee transactions on wireless communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.01
H-Index - 223
eISSN - 1558-2248
pISSN - 1536-1276
DOI - 10.1109/twc.2018.2890469
Subject(s) - stackelberg competition , computer science , backward induction , service provider , computer network , bilevel optimization , enhanced data rates for gsm evolution , wireless network , game theory , mobile network operator , service (business) , cache , cellular network , wireless , optimization problem , telecommunications , algorithm , business , microeconomics , marketing , economics
In a sponsored content scheme, a wireless network operator negotiates with a sponsored content service provider where the latter can pay the former to lower the cost of the mobile subscribers/users to access certain content. As such, the scheme motivates the entities in the sponsored content ecosystem to be more actively involved. Meanwhile, with the forthcoming 5G cellular networks, edge caching becomes a promising technology for traffic offloading to reduce cost and improve service quality of the content service. The key idea is that an edge caching content service provider caches content on edge networks. The cached content is then delivered to mobile users locally, reducing latency substantially. In this paper, we propose the joint sponsored and edge caching content service market model. We investigate an interplay between the sponsored content service provider and the edge caching content service provider under the non-cooperative game framework. Furthermore, the interactions among the wireless network operator, content service providers, and mobile users are modeled as a hierarchical three-stage Stackelberg game. In the game model, we analyze the sub-game perfect equilibrium in each stage through backward induction analytically. Additionally, the existence of the proposed Stackelberg equilibrium is validated by capitalizing on the bilevel optimization programming. Based on the analysis of the game properties, we propose a sub-gradient-based iterative algorithm, which guarantees to converge to the Stackelberg equilibrium.

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