© 2014 Dr. Adel Nadjaran ToosiCloud computing has introduced a major shift in the IT delivery model by offering computing resources for hosting applications as a utility. This helps businesses and organizations to access advanced IT facilities offered by cloud providers without the expensive up-front investments necessary to establish their own infrastructure. In this context, significant research efforts have already been made that aim to minimize costs for cloud customers; less attention however, has been given to challenges and opportunities that cloud providers face when striving for profit maximization.
This thesis presents a set of novel market and economics-inspired policies, mechanisms, algorithms, and software designed to address the profit maximization problem of Infrastructure-as-a-Service (IaaS) cloud providers. Our solutions are proposed for two main types of providers: 1) those who rely solely on their own resources to serve customers and 2) those who participate in a cloud federation and benefit from resource sharing. We explore different tools and methods such as resource provisioning mechanisms, financial option markets, revenue management systems, and mechanism design methods to achieve the goal of profit maximization. Our evaluation of the proposed solutions demonstrates that IaaS cloud providers can increase their Return on Investment (ROI) while honoring Quality of Service (QoS) requirements associated with customer applications.
In summary, the key contributions of this thesis towards profit maximization for IaaS cloud providers are: 1) resource provisioning policies that assist a provider in a cloud federation in deciding whether to reject, outsource or terminate spot instances to handle incoming requests; 2) a financial option-based market mechanism designed for futures trading of resources in a federated cloud environment; 3)  admission control algorithms embedded within a revenue management framework that supports a joint offering of usage-based, reservation-based and demand-oriented pricing models; 4) a multi-unit, online recurrent auction mechanism for selling spare capacity of a data center that is envy-free, truthful with high probability, and generates near optimal profit for the provider; and finally 5) an implementation of the proposed auction mechanism by identifying the Spot instance pricing as a Service (SipaaS) framework and its realization in OpenStack.Open Acces