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Dynamic Environment and Snowflake Schema in Real Time Data Services

by S. Aswini, D. Murali, R. Selvam
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 82 - Number 5
Year of Publication: 2013
Authors: S. Aswini, D. Murali, R. Selvam
10.5120/14113-2162

S. Aswini, D. Murali, R. Selvam . Dynamic Environment and Snowflake Schema in Real Time Data Services. International Journal of Computer Applications. 82, 5 ( November 2013), 23-29. DOI=10.5120/14113-2162

@article{ 10.5120/14113-2162,
author = { S. Aswini, D. Murali, R. Selvam },
title = { Dynamic Environment and Snowflake Schema in Real Time Data Services },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 82 },
number = { 5 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 23-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume82/number5/14113-2162/ },
doi = { 10.5120/14113-2162 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:59.716344+05:30
%A S. Aswini
%A D. Murali
%A R. Selvam
%T Dynamic Environment and Snowflake Schema in Real Time Data Services
%J International Journal of Computer Applications
%@ 0975-8887
%V 82
%N 5
%P 23-29
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The demand for real-time data service is increasing in many applications such as e-commerce, agile manufacturing, telecommunications, network management and transportation management. It is desirable but challenging, the workload may vary dynamically. In this paper we propose an approach for managing the dynamic environment using snowflake schema for real time database, that the dynamic environment operates an unpredictable environment such as they cannot predict accurate client request the stock quote at a moment of time. So they can implement dynamic workload adapting technique to improve the freshness of data in real-time and implement the technique called big bang adoption technique support the changes which are needed for a real changing process start . By Modeling database dynamic workload adoption in terms of the relation between data service delay and Conglomerate estimation. They also provide Quality Of Service to data guarantees for real-time data services. compare to most existing system feedback control representing , our dynamic snowflake schema significantly improves the average throughput.

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Index Terms

Computer Science
Information Sciences

Keywords

Big-bang adaption snow flake schema conglomerate.

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