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VIP: Virtual Performance-State for Efficient Power Management of Virtual Machines
- VIP: Virtual Performance-State for Efficient Power Management of Virtual Machines
- Kang, Ki Dong; Mohammad Alian; Kim, Daehoon; Huh, Jaehyuk; Nam Sung Kim
- DGIST Authors
- Kim, Daehoon
- Issue Date
- 2018 ACM Symposium on Cloud Computing, SoCC 2018, 237-248
- A power management policy aims to improve energy efficiency by choosing an appropriate performance (voltage/frequency) state for a given core. In current virtualized environments, multiple virtual machines (VMs) running on the same core must follow a single power management policy governed by the hypervisor. However, we observe that such a per-core power management policy has two limitations. First, it cannot offer the flexibility of choosing a desirable power management policy for each VM (or client). Second, it often hurts the power efficiency of some or even all VMs especially when the VMs desire conflicting power management policies. To tackle these limitations, we propose a per-VM power management mechanism, VIP supporting VIrtual Performance-state for each VM. Specifically, for VMs sharing a core, VIP allows each VM’s guest OS to deploy its own desired power management policy while preventing such VMs from interfering/influencing each other’s power management policy. That is, VIP can also facilitate a pricing model based on the choice of a power management policy. Second, identifying some inefficiency in strictly enforcing per-VM power management policies, we propose hypervisor-assisted techniques to further improve power and energy efficiency without compromising the key benefits of per-VM power management. To demonstrate the efficacy of VIP, we take a case that some VMs run CPU-intensive applications and other VMs run latency-sensitive applications sharing the same cores. Our evaluation shows that VIP reduces the overall energy consumption and improves the execution time of CPU-intensive applications compared with the default ondemand governor of Xen hypervisor up to 27% and 32%, respectively, without violating service level agreement (SLA) of latency-sensitive applications. © 2018 Association for Computing Machinery.
- Association for Computing Machinery, Inc
- Related Researcher
Kim, Dae Hoon
Computer Architecture and Systems Lab
Computer Architecture and Systems; Virtualization; Cloud Computing
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- Department of Information and Communication EngineeringComputer Architecture and Systems Lab2. Conference Papers
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