CP-CDN: Content Delivery Powered By Context and User Intelligence

Abstract

In order to improve end users' Web access experiences, today's Internet content providers generally employ Content Delivery Networks (CDNs) to provide material to end users. To comprehend reasons, methods, and amounts of CP-level intelligences may aid content distribution, we employ a measurement-based approach. The largest content provider in China, Tencent, constructed a CDN, which we first offer as a measurement study. Contrarily, CPCDN may leverage context intelligence—which captures how contents are constantly manipulated then synthesized in various circumstances —in order to optimise the user experience and service quality throughout content delivery since it is aware of the precise environment in which material is consumed. In this study, we use a measurement-based approach to reasons, methods, and amounts of CP-level information may aid content delivery in order to support the quick transition to CPCDN. We proactively replicate content based on interest groups based on crowd patterns so that users can access their desired content from nearby CPCDN servers. CPCDN is able to raise the level of both content delivery efficiency and user experience by using the potent user intelligence that captures how contents are constantly exchanged and disseminated across social networked users.