On the Incentive Mechanisms for Commercial Edge Caching in 5G Wireless Networks

Mobile data traffic has dramatically increased by a factor of around 100 over the last five years, while it is still expected to grow exponentially in the near future. Evidence indicates that the repetitive downloading of popular contents accounts for the increase in wireless traffic. This has consequently led to the development of edge caching technology for efficiently mitigating redundant transmissions from backbone networks by pre-caching frequently requested data at radio access networks. Among a variety of research topics in this field, the commercialization of edge caching has attracted augmented attention. In this article, we focus on the design of incentive mechanisms for commercial edge caching in 5G cellular networks, where the edge device providers (EDPs) and content providers (CPs) are the two counter-parties competing to maximize their own welfare. We first propose the architecture of a commercial caching system and analyze the revenue of the entities involved. Due to selfishness, each entity tries to achieve its highest benefit by squeezing profits from others, causing contentions of interest. Game theoretic approaches are then introduced to balance the conflicts. Four incentive frameworks are developed based on different categories of games in the context of the caching system. Afterward, we conduct case studies for three application scenarios to demonstrate the superiority of our proposed game models. Numerical results are also provided to validate the effectiveness of our proposed game frameworks.

[1]  Dong In Kim,et al.  Wireless backhauling of 5G small cells: challenges and solution approaches , 2015, IEEE Wireless Communications.

[2]  Xiaofei Wang,et al.  D2D Big Data: Content Deliveries over Wireless Device-to-Device Sharing in Large-Scale Mobile Networks , 2018, IEEE Wireless Communications.

[3]  Zhu Han,et al.  Wireless Distributed Storage in Socially Enabled D2D Communications , 2016, IEEE Access.

[4]  Xinbing Wang,et al.  On content-centric wireless delivery networks , 2014, IEEE Wireless Communications.

[5]  Zhu Han,et al.  Game Theory in Wireless and Communication Networks: Theory, Models, and Applications , 2011 .

[6]  Walid Saad,et al.  Matching theory for future wireless networks: fundamentals and applications , 2014, IEEE Communications Magazine.

[7]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[8]  He Chen,et al.  Pricing and Resource Allocation via Game Theory for a Small-Cell Video Caching System , 2016, IEEE Journal on Selected Areas in Communications.

[9]  Zhu Han,et al.  Design of Contract-Based Trading Mechanism for a Small-Cell Caching System , 2017, IEEE Transactions on Wireless Communications.

[10]  Zhu Han,et al.  Matching Theory: Applications in wireless communications , 2016, IEEE Signal Processing Magazine.

[11]  Mehdi Bennis,et al.  Living on the edge: The role of proactive caching in 5G wireless networks , 2014, IEEE Communications Magazine.

[12]  Dusit Niyato,et al.  Auction-based resource allocation in cognitive radio systems , 2012, IEEE Communications Magazine.

[13]  Xiaofei Wang,et al.  Collaborative Multi-Tier Caching in Heterogeneous Networks: Modeling, Analysis, and Design , 2017, IEEE Transactions on Wireless Communications.

[14]  Miao Pan,et al.  A Survey of Contract Theory-Based Incentive Mechanism Design in Wireless Networks , 2017, IEEE Wireless Communications.