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AutoTiering: Automatic Data Placement Manager in Multi-Tier All-Flash Datacenter
36th IEEE International Performance Computing and Communications Conference (IPCCC 2017) (2017)
  • Zhengyu Yang, Northeastern University
  • Morteza Hoseinzadeh
  • Allen Andrews
  • Clay Mayers
  • David Evans
  • Rory Bolt
Abstract
In the year of 2017, the capital expenditure of Flash-based Solid State Drivers (SSDs) keeps declining and the storage capacity of SSDs keeps increasing. As a result, the “selling point” of traditional spinning Hard Disk Drives (HDDs) as a backend storage – low cost and large capacity – is no longer unique, and eventually they will be replaced by low-end SSDs which have large capacity but perform orders of magnitude better than HDDs. Thus, it is widely believed that all-flash multi-tier storage systems will be adopted in the enterprise datacenters in the near future. However, existing caching or tiering solutions for SSD-HDD hybrid storage systems are not suitable for all-flash storage systems. This is because that all-flash storage systems do not have a large speed difference (e.g., 10x) among each tier. Instead, different specialties (such as high performance, high capacity, etc.) of each tier should be taken into consideration. Motivated by this, we develop an automatic data placement manager called “AutoTiering” to handle virtual machine disk files (VMDK) allocation and migration in an all-flash multi-tier datacenter to best utilize the storage resource, optimize the performance, and reduce the migration overhead. AutoTiering is based on an optimization framework, whose core technique is to predict VM’s performance change on different tiers with different specialties without conducting real migration. As far as we know, AutoTiering is the first optimization solution designed for all-flash multi-tier datacenters. We implement AutoTiering on VMware ESXi [1], and experimental results show that it can significantly improve the I/O performance compared to existing solutions.
Keywords
  • All-Flash Datacenter Storage,
  • Caching & Tiering Algorithm,
  • NVMe SSD,
  • Big Data,
  • Cloud Computing,
  • Resource Management,
  • I/O Workload Evaluation & Prediction
Disciplines
Publication Date
2017
Citation Information
Zhengyu Yang, Morteza Hoseinzadeh, Allen Andrews, Clay Mayers, et al.. "AutoTiering: Automatic Data Placement Manager in Multi-Tier All-Flash Datacenter" 36th IEEE International Performance Computing and Communications Conference (IPCCC 2017) (2017)
Available at: http://works.bepress.com/zhengyuyang/21/