Uniform price auction for allocation of dynamic cloud bandwidth

With the ubiquitous adoption of Cloud services by both companies and consumers alike, lack of an efficient system to explicitly price and allocate limited bandwidth has severely impacted the performance of Cloud user-applications. In this context, we consider a two-tier pricing model - consisting of Reservation Phase and Dynamic Phase - that caters to the needs of different kinds of applications. While the Reservation Phase can be used by Cloud users to obtain guarantees on minimum bandwidth well ahead in time, Dynamic Phase can be used to demand and obtain (possibly) additional bandwidth dynamically. Bandwidth being a limited resource, we develop a unique multi-stage uniform price auction with supply uncertainty to dynamically allocate bandwidth to users in the Dynamic Phase. We study the proposed model using a game theoretical approach. Our results prove that proposed auction mechanism is a promising approach for bandwidth allocation. We show that the model promotes the dual advantage of market efficiency and maximum revenue for the Cloud provider. We also demonstrate the price stability using numerical simulations. We argue that for rational, payoff-maximizing tenants of Cloud, the price is stable over the long run which makes the mechanism suitable for practical use.