Geodesic
An Optimized Method of HDFS for Massive Small Files Storage
Computer Science and Information Systems, Tome 15 (2018) no. 3.

Voir la notice de l'article provenant de la source Computer Science and Information Systems website

The development of the Internet-of-Things (IoT) and the Cyber-Physical System (CPS) has greatly facilitated many aspects of technological applications and development. This may lead to significant data growth, especially for small files. The analysis and processing of a large number of small files has become a crucial part of the development of IoT and CPS. Hadoop Distributed File Systems have become powerful platforms to store a larger amount of big data. However, this method has a number of issues when dealing with small files, such as substantial memory consumption and poor access. In this paper, a Dynamic Queue of Small Files (DQSF) algorithm is proposed to solve these problems. DQSF differentiates small files into different categories using an analytical hierarchal process that examines the performance of small files with different ranges across four indexes and determines the size of the dynamic queue according to the best system performance. Additionally, period classification is applied to preprocess the small files before storage, and the prefetching mechanism of the secondary index is used to process index tables. Experimental results show that this method could effectively reduce memory use and improve the storage efficiency of massive small files, which optimizes system performance.
Keywords: WSN, HDFS, massive small files, Dynamic Queue, Analytic Hierarchy Process 
@article{CSIS_2018_15_3_a6,
     author = {Weipeng Jing and Danyu Tong and GuangSheng Chen and Chuanyu Zhao and LiangKuan Zhu},
     title = {An {Optimized} {Method} of {HDFS} for {Massive} {Small} {Files} {Storage}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {15},
     number = {3},
     year = {2018},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a6/}
}
TY  - JOUR
AU  - Weipeng Jing
AU  - Danyu Tong
AU  - GuangSheng Chen
AU  - Chuanyu Zhao
AU  - LiangKuan Zhu
TI  - An Optimized Method of HDFS for Massive Small Files Storage
JO  - Computer Science and Information Systems
PY  - 2018
VL  - 15
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a6/
ID  - CSIS_2018_15_3_a6
ER  - 
%0 Journal Article
%A Weipeng Jing
%A Danyu Tong
%A GuangSheng Chen
%A Chuanyu Zhao
%A LiangKuan Zhu
%T An Optimized Method of HDFS for Massive Small Files Storage
%J Computer Science and Information Systems
%D 2018
%V 15
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a6/
%F CSIS_2018_15_3_a6
Weipeng Jing; Danyu Tong; GuangSheng Chen; Chuanyu Zhao; LiangKuan Zhu. An Optimized Method of HDFS for Massive Small Files Storage. Computer Science and Information Systems, Tome 15 (2018) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a6/