Deakin University
Browse

File(s) under permanent embargo

Scalable-DSP: a high scalable distributed storage and processing system for unstructured data in big data environments

conference contribution
posted on 2017-01-01, 00:00 authored by D Sun, Shang GaoShang Gao
High scalability is very important for an Internet-scale data storage and processing system in big data era. To achieve scalability, data-relevant issues are identified: unstructured data management, cost of data storage and processing, and cross-domain data management. In this paper, a high scalable distributed storage and processing system for unstructured data is proposed and developed. The paper includes the following contributions. (1) A high scalable distributed architecture is designed. (2) A multilevel, unstructured data storage system is built. (3) A distributed data processing system is implemented to verify the scalable architecture. Experimental results conclusively demonstrate the efficiency and effectiveness of the proposed storage and processing system, which achieves higher data storage efficiency and lower data access time objectives in Internet-scale big data environments.

History

Pagination

1-5

Location

Geelong, Vic.

Start date

2017-01-31

End date

2017-02-03

ISBN-13

9781450347686

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2017, ACM

Editor/Contributor(s)

[Unknown]

Title of proceedings

Proceedings of the Australasian Computer Science Week Multiconference

Event

Australasian Computer Science Week. Multiconference (2017 : Geelong, Vic.)

Publisher

ACM

Place of publication

New York, N.Y.

Series

ACM International Conference Proceeding Series