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Block I/O Scheduling on Storage Servers of Distributed File Systems

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Abstract

This paper presents a new scheme of I/O scheduling on storage servers of distributed/parallel file systems, for yielding better I/O performance. To this end, we first analyze read/write requests in the I/O queue of storage server (we name them block I/Os), by using our proposed technique of horizontal partition. Then, all block requests are supposed to be divided into multiple groups, on the basis of their offsets. This is to say, all requests related to the same chunk file will be grouped together, and then be satisfied within the same time slot between opening and closing the target chunk file on the storage server. As a result, the time resulted by completing block I/O requests can be significantly decreased, because of less file operations on the corresponding chunk files at the low-level file systems of server machines. Furthermore, we introduce an algorithm to rate a priority for each group of block I/O requests, and then the storage server dispatches groups of I/Os by following the priority order. Consequently, the applications having higher I/O priorities, e.g. they have less I/O operations and small size of involved data, can finish at a earlier time. We implement a prototype of this server-side scheduling in the PARTE file system, to demonstrate the feasibility and applicability of the proposed scheme. Experimental results show that the newly proposed scheme can achieve better I/O bandwidth and less I/O time, compared with the strategy of First Come First Served, as well as other server-side I/O scheduling approaches.

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Acknowledgments

This work was partially supported by “National Natural Science Foundation of China (No. 61303038)”, “Fundamental Research Funds for the Central Universities (No. XDJK2017B044)”, and “the Opening Project of State Key Laboratory for Novel Software Technology (No. KFKT2016B05)”.

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Authors and Affiliations

  1. The College of Computer and Information Science, Southwest University of China, Beibei, Chongqing, 400715, China

    Jianwei Liao

  2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, 210023, China

    Jianwei Liao

  3. The College of Computer Science and Engineering, Huaihua University, Huaihua, Hunan, 418008, China

    Dong Yin & Xiaoning Peng

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  1. Jianwei Liao
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Correspondence to Xiaoning Peng.

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Liao, J., Yin, D. & Peng, X. Block I/O Scheduling on Storage Servers of Distributed File Systems. J Grid Computing 16, 299–316 (2018). https://doi.org/10.1007/s10723-017-9423-1

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