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Improving Hypervisor Based SSD Caching with Logically Partitioned Blocks and Scanning in Cloud Environment

机译:通过逻辑分区块和云环境中的扫描来改进基于Hypervisor的SSD缓存

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In the era of big data and cloud computing the virtual machine (VM) environment is important where multiple VMs of different operating system and application can be simultaneously run on the same host. In the VM environment the conventional hard disk drive (HDD) has limitations such as low random access performance and high power consumption. Solid State Drive (SSD) is an emerging storage technology, playing a critical role in revolutionizing the storage system design. Recently, SSD storage caching is widely studied for VM-based systems. The existing works on cache space allocation identify the space demand of each VM based on hit ratio. They are not effective for the VMs of shared SSD cache due to the filte ring effect of higher-level caches. In this paper we propose a novel hypervisor-based SSD caching scheme, employing a new metric to accurately determine the demand on SSD cache space of each VM. Computer simulation confirms that it substantially improves the accuracy of cache space allocation compared to the existing schemes. It also allows to display comparable hit ratio as the existing schemes with less amount of SSD cache for the VMs.
机译:在大数据和云计算时代,虚拟机(VM)环境非常重要,其中不同操作系统和应用程序的多个VM可以在同一主机上同时运行。在VM环境中,常规硬盘驱动器(HDD)具有局限性,例如随机访问性能低和功耗高。固态硬盘(SSD)是一种新兴的存储技术,在彻底改变存储系统设计方面发挥着关键作用。最近,对于基于VM的系统,SSD存储缓存已得到广泛研究。现有的缓存空间分配工作基于命中率确定每个VM的空间需求。由于高级缓存的缓存效应,它们对于共享SSD缓存的VM无效。在本文中,我们提出了一种新颖的基于虚拟机管理程序的SSD缓存方案,该方案采用一种新的指标来准确确定每个VM对SSD缓存空间的需求。计算机仿真证实,与现有方案相比,它大大提高了缓存空间分配的准确性。它还可以显示与现有方案相当的命中率,而VM的SSD缓存较少。

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