High TPO/TCO for data storage: policy, algorithm and early practice

ZENG Lingfang1, FENG Dan1, JIANG Hong2

PDF(270 KB)
PDF(270 KB)
Front. Comput. Sci. ›› 2007, Vol. 1 ›› Issue (3) : 349-360. DOI: 10.1007/s11704-007-0034-z

High TPO/TCO for data storage: policy, algorithm and early practice

  • ZENG Lingfang1, FENG Dan1, JIANG Hong2
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Abstract

Today, the data storage industry faces a rapidly growing volume of data. Adding more primary disk capacity to manage data growth is a costly and non-sustainable strategy. Before investing in new capacity, data managers should rationalize their existing storage infrastructure to maximize the use of existing capacity. There is a growing need for achieving a high ratio of Total Performance of Ownership (TPO) to Total Cost of Ownership (TCO), or TPO/TCO. The storage infrastructure can be made more efficient by assessing data usages, eliminating unnecessary data copies, moving less critical data to less expensive disk devices and repurposing allocated but unused capacity. Optimizing existing storage assets can reduce storage costs by delaying or eliminating the need for new primary capacity to manage information growth. In this paper, we apply the notion of information lifecycle management (ILM) to achieve the above improved efficiencies and optimizations. By balancing data value and storage requirements, we aim to reduce the storage system s dependence on expensive high- performance disk devices and lower its cost per online gigabyte, thus resulting in a higher TPO/TCO.

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ZENG Lingfang, FENG Dan, JIANG Hong. High TPO/TCO for data storage: policy, algorithm and early practice. Front. Comput. Sci., 2007, 1(3): 349‒360 https://doi.org/10.1007/s11704-007-0034-z
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