SmartCuckoo: A Fast and Cost-Efficient Hashing Index Scheme for Cloud Storage Systems

Authors: 

Yuanyuan Sun and Yu Hua, Huazhong University of Science and Technology; Song Jiang, University of Texas, Arlington; Qiuyu Li, Shunde Cao, and Pengfei Zuo, Huazhong University of Science and Technology

Abstract: 

Fast query services are important to improve overall per- formance of large-scale storage systems when handling a large number of files. Open-addressing cuckoo hash schemes have been widely used to support query services due to the salient features of simplicity and ease of use. Conventional schemes are unfortunately inadequate to address the potential problem of having endless loops during item insertion, which degrades the query performance. To address the problem, we propose a cost- efficient cuckoo hashing scheme, named SmartCuckoo. The idea behind SmartCuckoo is to represent the hashing relationship as a directed pseudoforest and use it to track item placements for accurately predetermining the occurrence of endless loop. SmartCuckoo can efficiently predetermine insertion failures without paying a high cost of carrying out step-by-step probing. We have implemented SmartCuckoo in a large-scale cloud storage system. Extensive evaluations using three real- world traces and the YCSB benchmark demonstrate the efficiency and efficacy of SmartCuckoo. We have released the source code of SmartCuckoo for public use.

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BibTeX
@inproceedings {203247,
author = {Yuanyuan Sun and Yu Hua and Song Jiang and Qiuyu Li and Shunde Cao and Pengfei Zuo},
title = {SmartCuckoo: A Fast and Cost-Efficient Hashing Index Scheme for Cloud Storage Systems},
booktitle = {2017 {USENIX} Annual Technical Conference ({USENIX} {ATC} 17)},
year = {2017},
isbn = {978-1-931971-38-6},
address = {Santa Clara, CA},
pages = {553--565},
url = {https://www.usenix.org/conference/atc17/technical-sessions/presentation/sun},
publisher = {{USENIX} Association},
month = jul,
}

Presentation Audio