Optimal Disk Storage Allocation for Multitier Storage System

The current storage system is facing the bottleneck of performance due to the gap between fast CPU computing speed and the slow response time of hard disk. Recently a multitier hybrid storage system (MTHS) which uses fast flash devices like a solid-state drive (SSD) as the one of the high performanc...

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Vydáno v:IEEE transactions on magnetics Ročník 49; číslo 6; s. 2603 - 2609
Hlavní autoři: Shi, Haixiang, Arumugam, Rajesh Vellore, Foh, Chuan Heng, Khaing, Kyawt Kyawt
Médium: Journal Article Konferenční příspěvek
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.06.2013
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Cross-disciplinary physics: materials science; rheology
Disk storage allocation
Dynamic programming
Exact sciences and technology
Greedy algorithms
Hard disks
Heuristic algorithms
Information storage
knapsack problem
Magnetism
Materials science
multitier hybrid storage network
Other topics in materials science
Performance evaluation
Physics
Resource management
Studies
Vectors
Storage
knapsack problem
multitier hybrid storage network
dynamic programming
Disks
Disk storage allocation
Magnetic properties
ISSN:0018-9464, 1941-0069
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Shrnutí:The current storage system is facing the bottleneck of performance due to the gap between fast CPU computing speed and the slow response time of hard disk. Recently a multitier hybrid storage system (MTHS) which uses fast flash devices like a solid-state drive (SSD) as the one of the high performance storage tiers has been proposed to boost the storage system performance. In order to maintain the overall performance of the MTHS, optimal disk storage assignment has to be designed so that the data migrated to the high performance tier like SSD is the optimal set of data. In this paper we proposed a optimal data allocation algorithm for disk storage in MTHS. The data allocation problem (DAP) is to find the optimal lists of data files for each storage tier in the MTHS to achieve maximal benefit values without exceeding the available size of each tier. We formulate the DAP as a special multiple choice knapsack problem (MCKP) and propose the multiple-stage dynamic programming (MDP) to find the optimal solutions. The results show that the MDP can achieve improvements up to 6 times compared with the existing greedy algorithms.
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ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2013.2250936