How to place and deliver the videos through edge caching networks is a hot and open issue on releasing the heavy loads of backhaul link caused by explosive growth of data traffic and frequent requests. To address this issue, a joint video caching and transmission scheme is studied. In specific, the successful transmission probability, energy efficiency and system average delay are first derived based on the stochastic geometry theory. A video caching optimization problem is then formulated to balance the energy efficiency and system average delay. Considering the high complexity of the problem solution, we propose a genetic-based video placement and delivery algorithm to obtain a near-optimal solution. The accuracy of the proposed algorithm is finally validated by simulation results.

如何通过边缘缓存网络放置和交付视频，是释放因数据流量的爆炸性增长和频繁请求而造成的回程链路沉重负担的一个热门而开放的问题。为了解决这个问题，研究了联合视频缓存和传输方案。具体而言，首先基于随机几何理论推导成功的传输概率，能效和系统平均延迟。然后制定视频缓存优化问题，以平衡能效和系统平均延迟。考虑到问题解决方案的高度复杂性，我们提出了一种基于遗传的视频放置和交付算法来获得接近最优的解决方案。仿真结果最终验证了所提算法的准确性。