Today's Internet has witnessed an increase in the popularity of mobile video
streaming, which is expected to exceed 3/4 of the global mobile data traffic by
2019. To satisfy the considerable amount of mobile video requests, video
service providers have been pushing their content delivery infrastructure to
edge networks--from regional CDN servers to peer CDN servers (e.g.,
smartrouters in users' homes)--to cache content and serve users with storage
and network resources nearby. Among the edge network content caching paradigms,
Wi-Fi access point caching and cellular base station caching have become two
mainstream solutions. Thus, understanding the effectiveness and performance of
these solutions for large-scale mobile video delivery is important. However,
the characteristics and request patterns of mobile video streaming are unclear
in practical wireless network. In this paper, we use real-world datasets
containing 50 million trace items of nearly 2 million users viewing more than
0.3 million unique videos using mobile devices in a metropolis in China over 2
weeks, not only to understand the request patterns and user behaviors in mobile
video streaming, but also to evaluate the effectiveness of Wi-Fi and
cellular-based edge content caching solutions. To understand performance of
edge content caching for mobile video streaming, we first present temporal and
spatial video request patterns, and we analyze their impacts on caching
performance using frequency-domain and entropy analysis approaches. We then
study the behaviors of mobile video users, including their mobility and
geographical migration behaviors. Using trace-driven experiments, we compare
strategies for edge content caching including LRU and LFU, in terms of
supporting mobile video requests. Moreover, we design an efficient caching
strategy based on the measurement insights and experimentally evaluate its
performance.

本文研究通过对中国一座大都市两周之内的两百万用户观看约 30 万个唯一视频的真实数据集进行分析，提出了基于移动视频请求模式和边缘内容缓存影响的缓存策略，并且使用实验数据对其进行了验证。