Access Types Effect on Internet Video Services and Its Implications on CDN Caching

Abstract

Video providers heavily rely on geographically distributed content distribution networks (CDNs) to place video content as close to users as possible, with an aim of improving video quality and avoiding single point of failure at the server side. The effectiveness of CDNs is mostly dependent on the content consumption patterns. Currently, video providers are offering access to content from different platforms (e.g., mobile devices and PC clients), which might result in distinct video content consumption patterns and finally affect the efficiency of CDN caching. Nevertheless, the access type effect on Internet videos is not well understood. In this paper, using a data set consisting of 26 million video requests of a large-scale commercial video-on-demand system, we study the effect of three main access types, i.e., proprietary software on PC clients, Web browser, and mobile apps. Several observations suggest that access types should be considered carefully in CDN design. In particular, the user engagement, user interests in content, and video popularity dynamics patterns, three important factors for video caching, vary remarkably in the three access types. Leveraging off our findings, we propose an access type-aware CDN caching system that associates a cache for each access type and also several optimizations, including partial caching of videos based on chunk-level caching, cross-platform read-only cache access, and prefiltering of the least popular videos. Trace-driven simulations demonstrate that the access type-aware CDN caching achieves high cache hit rate and, more importantly, greatly reduces the disk load that is measured by the number of cache replacement operations.