Data and revenue management using tiered storage

Information lifecycle management is of critical importance to organizations with burgeoning data. As different groups of data assume different priorities within a firm, tiered storage emerges as a necessary and viable mechanism for data management. We consider the case of online video downloads and model data as a network where relationships between data nodes capture the impact on content usage and browsing habits. We devise a bi-level programming approach to solve the buyer's and the seller's problems by taking into consideration both direct and indirect hits to the specific data nodes. We model the seller as a revenue maximizer while the buyer is interested in maximizing the overall hits, especially to revenue generating data content. We provide a detailed analysis of the choices made by these two entities and provide a roadmap for the empirical analysis to be accomplished in future.