Socially-Aware Multimedia Content Delivery for the Cloud

Abstract

Most Content Delivery Networks (CDNs) are operated as a Software as a Service (SaaS): Many cloud providers build their custom CDNs to benefit from content users, as well as reduce demand on their own telecommunications infrastructure. More importantly, though, CDNs contribute to cloud adoption, as they can address network problems of cloud computing. With multimedia content providers requiring CDN services to enable the delivery of bandwindth-demanding media to end-users, and the growth of HTTP traffic due to media files circulating over Online Social Networks (OSNs), a social-awareness mechanism over a CDN becomes essential, to mitigate the considerable weight placed on bandwidth. A social awareness mechanism augmented to a stand-alone CDN traffic simulator addresses the issue of which content will be copied in the surrogate servers of a CDN infrastructure and to what extent. Hence, it ensures an optimized content diffusion placement. Herein, we further address the issue of temporal diffusion, related to the most efficient timing of the content placement. We exploit the knowledge of peak times for upload and download, so that content is prefetched in the hours with less traffic. We also incorporate other contextual information, such as the viewership within the media service, to ensure performance optimization. Our variations are experimentally proven to contribute toward maximization of CDNs' performance and minimization of content replication costs.