Economic models for cloud service markets: Pricing and Capacity planning

Cloud computing is a paradigm that has the potential to transform and revolutionalize the next generation IT industry by making software available to end-users as a service. A cloud, also commonly known as a cloud network, typically comprises of hardware (network of servers) and a collection of softwares that is made available to end-users in a pay-as-you-go manner. Multiple public cloud providers (ex., Amazon) co-existing in a cloud computing market provide similar services (software as a service) to its clients, both in terms of the nature of an application, as well as in quality of service (QoS) provision. The decision of whether a cloud hosts (or finds it profitable to host) a service in the long-term would depend jointly on the price it sets, the QoS guarantees it provides to its customers , and the satisfaction of the advertised guarantees. In the first part of the paper, we devise and analyze three inter-organizational economic models relevant to cloud networks. We formulate our problems as non co-operative price and QoS games between multiple cloud providers existing in a cloud market. We prove that a unique pure strategy Nash equilibrium (NE) exists in two of the three models. Our analysis paves the path for each cloud provider to know what prices and QoS level to set for end-users of a given service type, such that the provider could exist in the cloud market. A cloud provider services end-user requests on behalf of cloud customers, and due to the uncertainty in user demands over time, tend to overprovision resources like CPU, power, memory, storage, etc., in order to satisfy QoS guarantees. As a result of over-provisioning over long time scales, server utilization is very low and the cloud providers have to bear unnecessary wasteful costs. In this regard, the price and QoS levels set by the CPs drive the end-user demand, which plays a major role in CPs estimating the minimal capacity to meet their advertised guarantees. By the term ‘capacity’, we imply the ability of a cloud to process user requests, i.e., number of user requests processed per unit of time, which in turn determine the amount of resources to be provisioned to achieve a required capacity. In the second part of this paper, we address the capacity planning/optimal resource provisioning problem in single-tiered and multi-tiered cloud networks using a techno-economic approach. We develop, analyze, and compare models that cloud providers can adopt to provision resources in a manner such that there is minimum amount