An Economic Agent Maximizing Cloud Provider Revenues Under a Pay-as-you-Book Pricing Model by Felipe Díaz Sánchez, Elias A. Doumith, Sawsan Al Zahr, and Maurice Gagnaire.

Abstract: The Cloud computing paradigm offers the illusion of infinite resources accessible to end-users anywhere at anytime. In such dynamic environment, managing distributed heterogenous resources is challenging. A Cloud workload is typically decomposed into advance reservation and on-demand requests. Under advance reservation, end-users have the opportunity to reserve in advance the estimated required resources for the completion of their jobs without any further commitment. Thus, Cloud service providers can make a better use of their infrastructure while provisioning the proposed services under determined policies and/or time constraints. However, estimating end-users resource requirements is often error prone. Such uncertainties associated with job execution time and/or SLA satisfaction significantly increase the complexity of the resource management.