Video on Demand Hosted in Private Cloud: Availability Modeling and Sensitivity Analysis

Abstract

Cloud computing environments have recently emerged as a new computing paradigm for organizing a shared pool of servers in data centres into a cloud infrastructure that can provide on demand service utilities. Due to the business potential of the pay-per-use model, as well as the advantages of easy scalability, up-to-date Multimedia Services can rely on cloud infrastructures to offer a wide variety of services, like video streaming, where the user can access their videos from cloud environments. Hierarchical analytical models are effective tools to evaluate the availability of complex systems and services such as these. This paper proposes the application of availability models to a cloud environment designed for a video streaming service. The hierarchical models thus created comprise Reliability Block Diagrams (RBDs) and Markov chains. Sensitivity analysis's used to determine the parameters that cause the greatest impact on the availability. The results obtained from case studies clearly demonstrate that sensitivity analysis is a valuable tool for identifying which components require attention when attempting to achieve increased availability in a system.