Blockchain-Driven Contents Sharing Strategy for Wireless Cache-Enabled D2D Networks

Caching and sharing contents among mobile devices via wireless device-to-device (D2D) communications is a promising way to offload data traffic. In order to encourage more content sharing among mobile devices, we propose a blockchain incentive scheme in this paper, where the base station (BS) can allocate computing power to mine blockchain in a period of time and give this mining profit to the mobile devices that share contents with others via D2D communication. In order to maximize the total profit, we develop the caching placement schemes considering different relationships between the allocated computing power and the shared data size. For the linear relationship, we can obtain the closed form expression of the optimal caching scheme and find that the mobile device prefers to cache the popular contents. For the nonlinear relationship, the optimal problem can be effectively solved by difference of convex (DC) programming and the results reveal that the mobile device prefers to caching different contents.

[1]  Jian Zhou,et al.  Cognitive Relay Networks With Energy Harvesting and Information Transfer: Design, Analysis, and Optimization , 2016, IEEE Transactions on Wireless Communications.

[2]  Zhu Han,et al.  Optimal Pricing-Based Edge Computing Resource Management in Mobile Blockchain , 2017, 2018 IEEE International Conference on Communications (ICC).

[3]  Jun Rao,et al.  Optimal caching placement for D2D assisted wireless caching networks , 2015, 2016 IEEE International Conference on Communications (ICC).

[4]  Satoshi Nakamoto Bitcoin : A Peer-to-Peer Electronic Cash System , 2009 .

[5]  Zheng Chen,et al.  Probabilistic Caching in Wireless D2D Networks: Cache Hit Optimal Versus Throughput Optimal , 2016, IEEE Communications Letters.

[6]  Weimin Lei,et al.  Cache-Enabled Device to Device Networks With Contention-Based Multimedia Delivery , 2017, IEEE Access.

[7]  Hui Liu,et al.  Communications, Caching, and Computing for Mobile Virtual Reality: Modeling and Tradeoff , 2018, IEEE Transactions on Communications.

[8]  Cheng Li,et al.  Multi-User Scheduling of the Full-Duplex Enabled Two-Way Relay Systems , 2017, IEEE Transactions on Wireless Communications.

[9]  Chenyang Yang,et al.  High-Throughput Opportunistic Cooperative Device-to-Device Communications With Caching , 2016, IEEE Transactions on Vehicular Technology.

[10]  Zhiyong Chen,et al.  Design and Optimization of VoD Schemes With Client Caching in Wireless Multicast Networks , 2018, IEEE Transactions on Vehicular Technology.

[11]  Dusit Niyato,et al.  Social Welfare Maximization Auction in Edge Computing Resource Allocation for Mobile Blockchain , 2017, 2018 IEEE International Conference on Communications (ICC).

[12]  Victor C. M. Leung,et al.  Computation Offloading and Content Caching in Wireless Blockchain Networks With Mobile Edge Computing , 2018, IEEE Transactions on Vehicular Technology.

[13]  Yong Zhao,et al.  Interference Cancelation at Receivers in Cache-Enabled Wireless Networks , 2016, IEEE Transactions on Vehicular Technology.

[14]  Liang Qian,et al.  The three primary colors of mobile systems , 2016, IEEE Communications Magazine.

[15]  Yongming Huang,et al.  Hybrid Precoder Design for Cache-Enabled Millimeter-Wave Radio Access Networks , 2019, IEEE Transactions on Wireless Communications.

[16]  Zhu Han,et al.  Edge Computing Resource Management and Pricing for Mobile Blockchain , 2017, ArXiv.

[17]  Yong Zhao,et al.  Communication-Constrained Mobile Edge Computing Systems for Wireless Virtual Reality: Scheduling and Tradeoff , 2018, IEEE Access.

[18]  N. Houy The Economics of Bitcoin Transaction Fees , 2014 .