A Game-Theoretic Analysis of Pricing Strategies for Competing Cloud Platforms

In this paper, we analyse how multiple competing cloud platforms set effective service prices between Web service providers and consumers. We propose a novel economic framework to model this problem. Cloud platforms run double auction mechanisms, where Web service is commodity traded by service providers (sellers) and service consumers (buyers). Multiple cloud platforms compete against each other to attract service providers and consumers. Specifically, we use game theory to analyse the pricing policies of competing cloud platforms, where service providers and consumers can choose to participate in any of the platforms, and bid or ask for the Web service. The platform selection and bidding strategies of service providers and consumers are affected by the pricing policies and vice versa, and so we propose a co-learning algorithm based on fictitious play to analyse this problem. In more detail, we investigate a setting with two competing cloud platforms who can adopt either equilibrium k pricing policy or discriminatory k pricing policy. We find that, when both cloud platforms use the same type of pricing policy, they can co-exist in equilibrium, and they have an extreme bias to service providers or consumers when setting k. When both platforms adopt different types of policies, we find that all service providers and consumers converge to the discriminatory k pricing policy and so the two competing platforms can no longer co-exist.