Epidemic models using Resource Prediction mechanism for optimal provision of multimedia services

Abstract

This paper proposes a network architecture that goes a step beyond the current state-of-the-art, by elaborating on a novel resource reservation and provision scheme, through a Media Distribution Middleware (MDM), that is based on a Resource Prediction Engine (RPE) leading to both high resource utilization and quality guarantees. The architecture defines management planes and software components that provide the mechanisms for collecting monitoring data, predicting possible future values of the network metrics and resources usage, and applying management decisions to keep the provision optimal. The proposed research approach is based on novel time series and epidemic spread models, and the outcome is used for the optimal distribution of streaming data, among Content Delivery Networks, cloud-based providers and Home Media Gateways. The proposed epidemic diseases model adopts the characteristics of the multimedia content delivery over the network architecture. In this context, the paper aims to present the advantages of using such models, by presenting and analyzing an epidemic spread scheme for Video on Demand (VoD) delivery, to predict future epidemic spread behavior. The validity of the proposed system is verified through several sets of extended experimental simulation tests, carried out under controlled simulation conditions.