A Quantum-Inspired Evolutionary Computing Algorithm for Disk Allocation Method
Summary :
Based on a Quantum-inspired Evolutionary Algorithm (QEA), a new disk allocation method is proposed for distributing buckets of a binary cartesian product file among unrestricted number of disks to maximize concurrent disk I/O. It manages the probability distribution matrix to represent the qualities of the genes. Determining the excellent genes quickly makes the proposed method have faster convergence than DAGA. It gives better solutions and 3.2 - 11.3 times faster convergence than DAGA.
- Publication
- IEICE TRANSACTIONS on Information Vol.E86-D No.3 pp.645-649
- Publication Date
- 2003/03/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Databases
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Kyung-Ho KIM, Joo-Young HWANG, Kuk-Hyun HAN, Jong-Hwan KIM, Kyu-Ho PARK, "A Quantum-Inspired Evolutionary Computing Algorithm for Disk Allocation Method" in IEICE TRANSACTIONS on Information,
vol. E86-D, no. 3, pp. 645-649, March 2003, doi: .
Abstract: Based on a Quantum-inspired Evolutionary Algorithm (QEA), a new disk allocation method is proposed for distributing buckets of a binary cartesian product file among unrestricted number of disks to maximize concurrent disk I/O. It manages the probability distribution matrix to represent the qualities of the genes. Determining the excellent genes quickly makes the proposed method have faster convergence than DAGA. It gives better solutions and 3.2 - 11.3 times faster convergence than DAGA.
URL: https://global.ieice.org/en_transactions/information/10.1587/e86-d_3_645/_p
Copy
@ARTICLE{e86-d_3_645,
author={Kyung-Ho KIM, Joo-Young HWANG, Kuk-Hyun HAN, Jong-Hwan KIM, Kyu-Ho PARK, },
journal={IEICE TRANSACTIONS on Information},
title={A Quantum-Inspired Evolutionary Computing Algorithm for Disk Allocation Method},
year={2003},
volume={E86-D},
number={3},
pages={645-649},
abstract={Based on a Quantum-inspired Evolutionary Algorithm (QEA), a new disk allocation method is proposed for distributing buckets of a binary cartesian product file among unrestricted number of disks to maximize concurrent disk I/O. It manages the probability distribution matrix to represent the qualities of the genes. Determining the excellent genes quickly makes the proposed method have faster convergence than DAGA. It gives better solutions and 3.2 - 11.3 times faster convergence than DAGA.},
keywords={},
doi={},
ISSN={},
month={March},}
Copy
TY - JOUR
TI - A Quantum-Inspired Evolutionary Computing Algorithm for Disk Allocation Method
T2 - IEICE TRANSACTIONS on Information
SP - 645
EP - 649
AU - Kyung-Ho KIM
AU - Joo-Young HWANG
AU - Kuk-Hyun HAN
AU - Jong-Hwan KIM
AU - Kyu-Ho PARK
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E86-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2003
AB - Based on a Quantum-inspired Evolutionary Algorithm (QEA), a new disk allocation method is proposed for distributing buckets of a binary cartesian product file among unrestricted number of disks to maximize concurrent disk I/O. It manages the probability distribution matrix to represent the qualities of the genes. Determining the excellent genes quickly makes the proposed method have faster convergence than DAGA. It gives better solutions and 3.2 - 11.3 times faster convergence than DAGA.
ER -
English
