Exploiting user preferences to reduce bandwidth requirements for VoD services with client caching

Abstract

Internet traffic is already dominated by video streaming applications. The quality of transmitted videos and the number of content available online is expected to increase in the upcoming years, which will further pressure the available network infrastructures. In this scenario, Video-on-Demand services require that distribution mechanisms improve the efficiency of video transmission, which impacts the network performance and system scalability. The efficiency of distribution is strongly related to the operating costs of the providers of such services. The most efficient methods available for Video-on-Demand distribution use strategies that combine multicast transmission and the storage capacity of the user's equipment. This paper presents a new method for Video-on-Demand distribution that explores the client storage capabilities by modelling the users' preferences with a Hidden Markov Model. The efficiency of the proposed method is demonstrated through computational simulations of different scenarios, including a sample of real users' activity. Our results indicate that the proposed scheme substantially outperforms the current Video-on-Demand distribution mechanisms in terms of network bandwidth consumption, significantly reducing operation costs by improving the system scalability.