Task-aware virtual machine scheduling for I/O performance

The use of virtualization is progressively accommodating diverse and unpredictable workloads as being adopted in virtual desktop and cloud computing environments. Since a virtual machine monitor lacks knowledge of each virtual machine, the unpredictableness of workloads makes resource allocation difficult. Particularly, virtual machine scheduling has a critical impact on I/O performance in cases where the virtual machine monitor is agnostic about the internal workloads of virtual machines. This paper presents a task-aware virtual machine scheduling mechanism based on inference techniques using gray-box knowledge. The proposed mechanism infers the I/O-boundness of guest-level tasks and correlates incoming events with I/O-bound tasks. With this information, we introduce partial boosting, which is a priority boosting mechanism with tasklevel granularity, so that an I/O-bound task is selectively scheduled to handle its incoming events promptly. Our technique focuses on improving the perf...

• Type: Conference
• Year: 2009
• Where: VEE
• Authors: Hwanju Kim, Hyeontaek Lim, Jinkyu Jeong, Heeseung Jo, Joonwon Lee
• Keywords: VEE 2009, Virtual Machine, Virtual Machine Monitor, Virtual Machine Scheduling, Virtualization