The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2017.080552
PDF

SaaS Level based Middleware Database Integrator Platform

Author 1: Sanjkta Pal

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 5, 2017.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: In purpose of data searching acceleration, the fastest data response is the major concern for latest cloud environment. Regarding this, the intellectual decision is to enrich the SaaS level applications. Amongst the SaaS based applications, service level database integration is the recent trend to provide the integrated view of the heterogeneous cloud databases through shared services using DBaaS. But the generic limitations interacted during the database integration are dynamic adaptability of multiple databases structure, dynamic data location identification in the concern databases, data response using the data commonality. Data migration technique and single query approach are the two individual solutions for the proposed limitations. But the side effects during data migration technique are extra space utilisation and excess time consumption. Again, the single query approach suffers from worst case time complexity for data connectivity, data aggregation and query evaluation. So, to find a suitable data response solution by eliminating these combined major issues, a graph based Middleware Database Integrator Platform or MDIP model has been proposed. This integrator platform is actually the flexible metadata representation technique for the concerned heterogeneous cloud databases. The associativity and commonality among components of multiple databases would be further helpful for efficient data searching in an integrated way. For the incorporation within the service level but not in the services, MDIP is considered as the different platform. It is applicable over any service based database integration in purpose of data response efficiency. Finally, the quality assessment using evaluated query time compared with already proposed SLDI shows better data access quality. Thus, its expertise dedication in data response can overcome summarised challenges like data adaptation flexibility, dynamic identification of data location, wastage of data storage, data accessing within minimal time span and optimised cost in presence of data consistency, data partitioning and user side scalability.

Keywords: Database integration; Integrator platform; Multi- Level graph; Subset of vertices; First class edge; Concrete edge; Connectivity edge

Sanjkta Pal, “SaaS Level based Middleware Database Integrator Platform” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080552

@article{Pal2017,
title = {SaaS Level based Middleware Database Integrator Platform},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080552},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080552},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Sanjkta Pal}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Computer Vision Conference
  • Healthcare Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org