With the enormous and increasing user demand, I/O performance is one of the primary considerations to build a data center. Several new technologies in data centers, such as tiered storage, prompt the widespread usage of multilevel cache techniques. In these storage systems, the upper level storage typically serves as a cache for the lower level, which forms a distributed multilevel cache system. However, although many excellent multilevel cache algorithms have been proposed to improve the I/O performance, they still have potential to be enhanced by investigating the history information of hints. To address this challenge, in this paper, we propose a novel hint frequency based approach (HFA), to improve the overall multilevel cache performance of storage systems. The main idea of HFA is using hint frequencies (the total number of demotions/promotions by employing demote/promote hints) to efficiently explore the valuable history information of data blocks among multiple levels. HFA can be applied with several popular multilevel cache algorithms, such as Demote, Promote and Hint-K. Simulation results show that, compared with original multilevel cache algorithms such as Demote, Promote and Hint-K, HFA can improve the I/O performance by up to 20% under different I/O workloads.
This work was supported by the National Basic Research 973 Program of China under Grant No. 2015CB352403, the National High Technology Research and Development 863 Program of China under Grant No. 2015AA015302, the National Natural Science Foundation of China under Grant Nos. 61332001, 61303012, 61572323 and 61628208, the Scientific Research Foundation for the Returned Overseas Chinese Scholars, and the CCF-Tencent Open Fund.
通讯作者: Chen-Tao Wu
About author: Xiao-Dong Meng is a Ph.D. student of computer science in Shanghai Jiao Tong University. He received his Bachelor's degree in electronic information science and technology from Wuhan University in 2007, and Master's degree in information technology from Monash University, Melbourne, in 2010. His main interest is in parallel and distributed computing, social graph processing, and storage systems.
Xiao-Dong Meng, Chen-Tao Wu, Min-Yi Guo, Jie Li, Xiao-Yao Liang, Bin Yao, Long Zheng.一种基于标签频率的多级存储系统IO性能的改进方法[J] Journal of Computer Science and Technology , 2017,V32(2): 312-328
Xiao-Dong Meng, Chen-Tao Wu, Min-Yi Guo, Jie Li, Xiao-Yao Liang, Bin Yao, Long Zheng.A Hint Frequency Based Approach to Enhancing the I/O Performance of Multilevel Cache Storage Systems[J] Journal of Computer Science and Technology, 2017,V32(2): 312-328
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