Video scene identification and classification for user-tailored QoE in GEO satellites

Abstract

Satellite networks offer an efficient alternative where no terrestrial networks are available, and can offer a cost effective means of transferring data. Numerous proposals have addressed the problem of resource allocation in geostationary (GEO) satellites, and have been evaluated via various performance metrics related to user Quality of Service (QoS). However, ensuring that on average the users’ QoS requirements are satisfied does not guarantee the satisfaction of their individual Quality of Experience (QoE) requirements, especially in the case of bursty video users. This paper proposes the use of video scene identification and classification for traffic modeling at the scene level in order to improve resource allocation and user QoE in GEO satellite networks. The proposed call admission control and medium access control framework makes decisions based on available bandwidth, long-term and short-term user satisfaction and the revenue that the provider may gain.

An Efficient and Energy-Aware Cloud Consolidation Algorithm for Multimedia Big Data Applications

“…Multimedia big data introduces new kinds of multimedia services. Some of multimedia big data applications include digital image processing [11], audio/video recommendations [12], video annotation [13], online advertisements [14], video classification [15], and multimedia delivery for mobile devices [16]. Therefore, cloud computing gains wide acceptance for processing multimedia big data since it provides a number of benefits, including reduced IT costs, flexibility, and increased collaboration [17].…”