遗传算法在I/O调度策略中的应用与研究

吕燕彬; 秦品乐

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遗传算法在I/O调度策略中的应用与研究

更新时间：2026-09-04

- 遗传算法在I/O调度策略中的应用与研究
- Research and Application of Genetic Algorithm in I/O Schedule Strategy
- 微电子学与计算机 2016年33卷第3期页码：116-120
- 作者机构：
  
  中北大学机构计算机与控制工程学院,山西,太原,030051
- 作者简介：
- 基金信息：
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- 纸质出版：2016
- 稿件说明：
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吕燕彬, 秦品乐. 遗传算法在I/O调度策略中的应用与研究[J]. 微电子学与计算机, 2016, 33(3): 116-120.

LV Yan-bin, QIN Pin-le. Research and Application of Genetic Algorithm in I/O Schedule Strategy[J]. 2016, 33(3): 116-120.
吕燕彬, 秦品乐. 遗传算法在I/O调度策略中的应用与研究[J]. 微电子学与计算机, 2016, 33(3): 116-120. DOI：

LV Yan-bin, QIN Pin-le. Research and Application of Genetic Algorithm in I/O Schedule Strategy[J]. 2016, 33(3): 116-120. DOI：

摘要

将遗传算法的思想应用到I/O调度策略的多参数调整过程中

使策略参数根据存储系统I/O操作的阶段性统计量进行多轮迭代

最终筛选出能够最优适应存储系统实时运行环境的策略参数

发挥出最优的I/O调度性能.改进后的I/O调度策略能够在较短时间内使策略参数收敛.实验结果表明

在长时间、重负载运行的存储系统中

使用所提出的调度策略比使用原有调度策略有明显的I/O性能提升.

Abstract

In this paper

by applying the conception of genetic algorithm into the parameters turning process of I/O schedule strategy

it takes strategy parameters adapting the storage system according to the periodical statistic of I/O operation

and got a group of strategy parameters

which have the best adaption in real-time storage environment

and makes the I/O schedule strategy have a better performance. In the new way of tuning strategy parameters

it makes the strategy parameters resuming its convergence in a short time. The experimental results show that

in the storage system which is running long term and have a heavy load

the efficiency of computers I/O operation which applies this papers strategy has an obvious performance promotion than applying others.

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references

Schindler J, Shete S, Smith K A. Improving throughput for small disk requests with proximal i/o[C]//Proceedings of the 9th USENIX Conference on File and Storage Technologies(FAST'2011)San Jose, CA. IEEE, 2011: 133-147.

刘硕. 高清视频服务器磁盘I/O调度算法的研究[D]. 厦门: 厦门大学, 2014.

Dunn M, Reddy A L N. A new I/O scheduler for solid state devices. Technical Report TAMU-ECE-2009-02 of Electrical and Computer Engineering[R]. 2009.

Park S, Shen K. FIOS: A fair, efficient flash i/o scheduler[C]//Proceedings of the 10th USENIX Conference on File and Storage Technologies C. Berkeley, CA, USA: ACM, 2012: 13-13.

Murat A, Novruz A. Development a new mutation operator to solve the traveling salesman problem by aid of genetic algorithms[J]. Expert System with Applications, 2011, 38(3): 1313-1320. DOI: 1313

Zhang X, Davis K, Jiang S. Itransformer: Using SSD to improve disk scheduling for high-performance I/O[C]//Proceedings of the 26th IEEE International Parallel and Distributed Processing Symposium Shanghai, China: IEEE, 2012: 715-726.

LIFa-chao, XU Li-da, JIN Chen-xia, et al. Intelligent bionic genetic algorithm (IB-GA) and its convergence[J]. Expert System with Applications, 2011, 38(7): 8804-8811. DOI: 8804

Kim J, Seo S, Jung D, et al. Parameter-aware I/O management for solid state disk[J]. IEEE Trans on Computers, 2012, 61(5): 636-649. DOI: 636

梁昔明, 朱灿, 颜东煌. 基于物种选择的遗传算法求解约束非线性规划问题[J]. 中南大学学报: 自然科学版, 2009, 40(1): 185-189. DOI: 185

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