An Application-Oriented Cache Allocation and Prefetching Method for Long-Running Applications in Distributed Storage Systems

GUO Chang; LI Ying; LIU Hongzhi; WU Zhonghai

doi:10.1049/cje.2019.05.004

Volume 28 Issue 4

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Article Navigation > Chinese Journal of Electronics > 2019 > 28(4): 773-780

GUO Chang, LI Ying, LIU Hongzhi, et al., “An Application-Oriented Cache Allocation and Prefetching Method for Long-Running Applications in Distributed Storage Systems,” Chinese Journal of Electronics, vol. 28, no. 4, pp. 773-780, 2019, doi: 10.1049/cje.2019.05.004

Citation:

GUO Chang, LI Ying, LIU Hongzhi, et al., “An Application-Oriented Cache Allocation and Prefetching Method for Long-Running Applications in Distributed Storage Systems,” Chinese Journal of Electronics, vol. 28, no. 4, pp. 773-780, 2019, doi: 10.1049/cje.2019.05.004

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An Application-Oriented Cache Allocation and Prefetching Method for Long-Running Applications in Distributed Storage Systems

doi: 10.1049/cje.2019.05.004

1.
School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;
2.
National Engineering Research Center For Software Engineering, Peking University, Beijing 100080, China;
3.
School of Software and Microelectronics, Peking University, Beijing 102600, China

Funds: This work is supported by the National Key R&D Program of China (No.2017YFB1002002).

Received Date: 2018-05-11
Rev Recd Date: 2018-08-14
Publish Date: 2019-07-10

Abstract

Abstract

Characteristics of long-running applications in cloud and big data environment are various and significantly influence the performance of cache systems. The gap between existing cache systems and the increasing performance requirements motivates us to propose the Application-oriented cache allocation and prefetching method (ACAP) to improve data access performance. An application-oriented cache allocation approach is designed based on hit count growth rates for a higher overall hit rate. Two application-oriented sequential prefetching approaches are proposed to improve the hit rate and prefetching accuracy by learning average read sizes of long-running applications. Based on correlation of data accesses, a parallelized correlated-directed prefetching approach is proposed to further increase the hit rate. Above approaches are intergrated to obtain the maximized hit rate and prefetching accuracy. Experimental results on 12 public real system traces show that ACAP achieves 14.03% (up to 33.82%) higher prefetching accuracy and 2.01% (up to 7.54%) higher hit rate compared with the best combination of baselines.
- Cache prefetching,
- Cache allocation,
- Distributed storage system,
- Resource management

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