A preemptive truthful VMs allocation online mechanism in private cloud

During the last decade, cloud-technology has presented considerable opportunities for high-performance computing (HPC). In addition, technical computing data centers have been able to maximize their return on investment (ROI). HPC system managers can leverage the benefits of a cloud model for their traditional HPC environments to improve scalability, simplify service access, accelerate collaboration or funding, enable pay-for-use, and improve efficiency. Many HPC clouds assume the form of private Infrastructure as a Service (IaaS). In practice, private cloud users may strategically misreport task values in order to achieve a high profit, and thus cloud providers cannot simply maximize the sum of allocated users' value, which is called social welfare. For this reason, designing a mechanism that reveals the truthful value of users with a concern for both random arrival tasks and maximizing social welfare is necessary. In this study, a model of an online mechanism for virtual machines allocation is built, a preemptive online mechanism is proposed, the truthfulness is proved, a competitive ratio is given, and several simulations are conducted using real tasks from a data center. The total values and completed tasks are compared to the online and offline allocations, respectively, according to different capacity. The simulations reveal that our mechanism is more efficient than the offline mechanism.