Content Rating Technique for Cloud-Oriented Content Delivery Network Using Weighted Slope One Scheme

摘要

Arguably, the rise in global population has been matched by the rapid rate of expansion of internet. Today, some of the prominent companies in information and media technology rely on content and advertising to fuel their growth. On the other hand, the insatiable thirst for information coupled with an incessant urge for instant consumption of digital media have made it impossible to overlook content delivery networks. As a cost-effective and robust means, cloud-based content delivery network (CCDN) service has considerable advantages. At the core of a CCDN service, lies a cloud-based data center infrastructure. This makes it possible to distribute content load over a large number of storage servers situated at various geographical locations. However, close on the heels of the advantages offered by CCDN service, comes an interminable challenge to stay ahead of high latency when meeting content delivery requests. We propose a collaborative filtering algorithm using weighted slope one method as a model to arrest network latency and optimize storage requirements. Our model demonstrates that it is able to stay ahead of over fitting, and increase accuracy of the results yielded. Using our approach, CCDN service providers will be able to boost content delivery speeds through determination of storage requirements in a flexible and cost-effective manner.