NDLI: S-CAVE: effective SSD caching to improve virtual machine storage performance

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ThermOS: system support for dynamic thermal management of chip multi-processors

APOGEE: adaptive prefetching on GPUs for energy efficiency

S-CAVE: effective SSD caching to improve virtual machine storage performance

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Meeting midway: improving CMP performance with memory-side prefetching

McRouter: multicast within a router for high performance network-on-chips

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S-CAVE: effective SSD caching to improve virtual machine storage performance

Content Provider	ACM Digital Library
Author	Zhang, Xiaodong Luo, Tian Ma, Siyuan Liu, Deng Lee, Rubao Zhou, Li
Abstract	A unique challenge for SSD storage caching management in a virtual machine (VM) environment is to accomplish the dual objectives: maximizing utilization of shared SSD cache devices and ensuring performance isolation among VMs. In this paper, we present our design and implementation of S-CAVE, a hypervisor-based SSD caching facility, which effectively manages a storage cache in a Multi-VM environment by collecting and exploiting runtime information from both VMs and storage devices. Due to a hypervisor's unique position between VMs and hardware resources, S-CAVE does not require any modification to guest OSes, user applications, or the underlying storage system. A critical issue to address in S-CAVE is how to allocate limited and shared SSD cache space among multiple VMs to achieve the dual goals. This is accomplished in two steps. First, we propose an effective metric to determine the demand for SSD cache space of each VM. Next, by incorporating this cache demand information into a dynamic control mechanism, S-CAVE is able to efficiently provide a fair share of cache space to each VM while achieving the goal of best utilizing the shared SSD cache device. In accordance with the constraints of all the functionalities of a hypervisor, S-CAVE incurs minimum overhead in both memory space and computing time. We have implemented S-CAVE in vSphere ESX, a widely used commercial hypervisor from VMWare. Our extensive experiments have shown its strong effectiveness for various data-intensive applications.
Starting Page	103
Ending Page	112
Page Count	10
File Format	PDF
ISBN	9781479910212
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-10-07
Access Restriction	Subscribed
Subject Keyword	Storage Ssd Virtual machine I/o Performance Cache
Content Type	Text
Resource Type	Article

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