@inproceedings{89dd4820840247069af15095f49637da,
title = "An effective grouping method for unstructured data based on Swift",
abstract = "Unstructured data is one of the most prominent buzzwords of this era, and from the business to the personal computer, unstructured data is ubiquitous and growing exponentially, managing these data and improving the access performance of these unstructured data is Critical. This paper is based on Swift which is the object storage service of open source cloud computing platform OpenStack, with the help of object storage framework, the use of grouping-based machine learning technology and the corresponding prefetching cache strategy to improve the access performance of unstructured data. Experimentally verify the performance improvement of the proposed method with respect to memory consumption, cache hit ratio, and latency of requests. Experimental results show that the proposed method can effectively reduce the cache consumption and request delay time and can greatly improve the cache hit rate.",
keywords = "Data prefetching, Grouping, Swift, Unstructured data",
author = "Miaomiao Dai and Dongjie Zhu",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 2018 International Conference on Computing and Data Engineering, ICCDE 2018 ; Conference date: 04-05-2018 Through 06-05-2018",
year = "2018",
month = may,
day = "4",
doi = "10.1145/3219788.3219791",
language = "英语",
isbn = "9781450363938",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "34--38",
booktitle = "ICCDE 2018 - International Conference on Computing and Data Engineering",
address = "美国",
}