An adaptive pricing scheme for content delivery systems

Content delivery has become an important enterprise on the Internet. There exists a huge demand for bandwidth-intensive, rich multimedia content like news, entertainment services and software. Two key issues associated with any content-delivery system are: revenue and user satisfaction. In this paper, we explore the domain of pricing for content delivery, and how it relates to revenue, and system utilization. A fundamental contribution of this paper is to consider a probabilistic user behavior model where users can refuse the offered service based on their capacity to pay and the price quoted. As a first step, we consider a system which delivers multimedia content on a First-Come-First-Served basis, and analyze pricing mechanisms which maximize the expectation of revenue. We argue that charging a constant price based on the customers' capacities to pay maximizes the expected revenue. Since the customers' capacities are highly varying and not known beforehand, we develop an adaptive pricing model and validate it using simulation. Our simulation results indicate that the adaptive pricing scheme generates nearly the same revenue as the theoretical expectation.