School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Chongqing Engineering Research Center of Communication Software, Chongqing 400065, China.
Sensors (Basel). 2018 Oct 10;18(10):3389. doi: 10.3390/s18103389.
There are a large number of redundant transmissions in current D2D multicast content delivery systems, which seriously reduces the utilization efficiency of resources. This paper designs a novel user-information-aware D2D video distribution mechanism. More specifically, by predicting users' video requests, the video can be pushed to potential service requesters while distributing video for service requesters. Firstly, the willingness of potential requesters to accept the pushed video is estimated based on the users' interests, the popularity of the videos and the residual-energy of the users' devices, and the user-demand-aware clustering algorithm is proposed. Secondly, considering social and interference information, the utility metric of D2D multicast is proposed to measure the value of content distribution service. Finally, this paper proposes a D2D video distribution mechanism to optimize the utility value. Simulation results show that the proposed mechanism significantly improves throughput, energy and spectrum efficiency compared to the traditional distribution mechanism.
当前的 D2D 多播内容分发系统中存在大量的冗余传输，这严重降低了资源的利用效率。本文设计了一种新颖的用户信息感知的 D2D 视频分发机制。更具体地说，通过预测用户的视频请求，可以在为服务请求者分发视频的同时将视频推送给潜在的服务请求者。首先，根据用户的兴趣、视频的流行度和用户设备的剩余能量，估计潜在请求者接受推送视频的意愿，并提出用户需求感知聚类算法。其次，考虑到社会和干扰信息，提出了 D2D 多播的效用度量来衡量内容分发服务的价值。最后，提出了一种 D2D 视频分发机制来优化效用值。仿真结果表明，与传统分发机制相比，所提出的机制显著提高了吞吐量、能量和频谱效率。
