Doris: An Adaptive Soft Real-Time Scheduler in Virtualized Environments

With the development of cloud computing and virtualization technologies, more and more soft real-time applications, such as Voice over Internet Protocol (VoIP) server and cloud gaming, are running in virtualized data centers. Though previous studies optimize CPU schedulers of hypervisors to support these applications in virtualized environments, there are some important challenges in designing an efficient CPU scheduler which is suitable for real-world clouds. On one hand, hypervisors do not know whether an application in a virtual machine (VM) has real-time requirements, so manually setting the scheduling parameters is a common case for CPU schedulers, which probably increases users' burden, lacks flexibility, and causes misconfigurations. On the other hand, it has been reported that most of existing CPU schedulers designed for soft real-time applications have an obvious propensity to such applications which prevents them from being applied in practical multi-tenant cloud environments. In this paper, we design and implement an adaptive soft real-time scheduler based on Xen, named Doris, to address these challenges. It identifies the VMs running soft real-time applications (RT-VMs) and infers their scheduling parameters according to the communication behaviors of VMs adaptively. Then, it promotes the priorities of VCPUs of the RT-VMs temporarily according to I/O events and the inferred scheduling parameters of RT-VMs to support soft real-time applications adaptively while minimizing the impacts on non-real-time applications. Finally, considering the importance of privileged entities (such as Domain0 in Xen) in I/O processing, Doris sets their types and scheduling parameters dynamically, which enables the adaptive scheduling of them to guarantee the performance of soft real-time applications. Our evaluation shows Doris can support soft real-time applications adaptively and efficiently, and only introduces very slight overhead.