I/O Workload Management for All-Flash Datacenter Storage Systems Based on Total Cost of Ownership

被引:1
作者
Yang, Zhengyu [1 ]
Awasthi, Manu [2 ]
Ghosh, Mrinmoy [3 ]
Bhimani, Janki [1 ]
Mi, Ningfang [1 ]
机构
[1] Northeastern Univ, Boston, MA 02115 USA
[2] Ashoka Univ, Sonipat 131029, Haryana, India
[3] Samsung Semicond Inc, San Jose, CA 95134 USA
基金
美国国家科学基金会;
关键词
Resource management; Throughput; Data models; Servers; Big Data; Measurement; Cloud computing; Flash resource management; total cost of ownership model; SSD write amplification; NVMe; wearout prediction; workload sequentiality pattern; data center storage system; RAID; PERFORMANCE;
D O I
10.1109/TBDATA.2018.2871114
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, the capital expenditure of flash-based Solid State Driver (SSDs) keeps declining and the storage capacity of SSDs keeps increasing. As a result, all-flash storage systems have started to become more economically viable for large shared storage installations in datacenters, where metrics like Total Cost of Ownership (TCO) are of paramount importance. On the other hand, flash devices suffer from write amplification, which, if unaccounted, can substantially increase the TCO of a storage system. In this paper, we first develop a TCO model for datacenter all-flash storage systems, and then plug a Write Amplification model (WAF) of NVMe SSDs we build based on empirical data into this TCO model. Our new WAF model accounts for workload characteristics like write rate and percentage of sequential writes. Furthermore, using both the TCO and WAF models as the optimization criterion, we design new flash resource management schemes (minTCO) to guide datacenter managers to make workload allocation decisions under the consideration of TCO for SSDs. Based on that, we also develop minTCO-RAID to support RAID SSDs and minTCO-Offline to optimize the offline workload-disk deployment problem during the initialization phase. Experimental results show that minTCO can reduce the TCO and keep relatively high throughput and space utilization of the entire datacenter storage resources.
引用
收藏
页码:332 / 345
页数:14
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