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Ranking Prediction for Cloud Services from The Past Usages

G.P. Kumar1 , K. Morarjee2

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-9 , Page no. 22-25, Sep-2014

Online published on Oct 04, 2014

Copyright © G.P. Kumar, K. Morarjee . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: G.P. Kumar, K. Morarjee , “Ranking Prediction for Cloud Services from The Past Usages,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.9, pp.22-25, 2014.

MLA Style Citation: G.P. Kumar, K. Morarjee "Ranking Prediction for Cloud Services from The Past Usages." International Journal of Computer Sciences and Engineering 2.9 (2014): 22-25.

APA Style Citation: G.P. Kumar, K. Morarjee , (2014). Ranking Prediction for Cloud Services from The Past Usages. International Journal of Computer Sciences and Engineering, 2(9), 22-25.

BibTex Style Citation:
@article{Kumar_2014,
author = {G.P. Kumar, K. Morarjee },
title = {Ranking Prediction for Cloud Services from The Past Usages},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2014},
volume = {2},
Issue = {9},
month = {9},
year = {2014},
issn = {2347-2693},
pages = {22-25},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=247},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=247
TI - Ranking Prediction for Cloud Services from The Past Usages
T2 - International Journal of Computer Sciences and Engineering
AU - G.P. Kumar, K. Morarjee
PY - 2014
DA - 2014/10/04
PB - IJCSE, Indore, INDIA
SP - 22-25
IS - 9
VL - 2
SN - 2347-2693
ER -

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Abstract

Web services are loosely-coupled software systems considered hold up interoperable machine-to-machine communication over a system. The most undemanding approach personalized cloud service quality of service ranking is to assess the entire service candidates at user side and position services base on observed values of quality of service. The materialization of web services has produces unprecedented prospect for organizations to setup additional agile as well as versatile collaborations with other organizations. Comparable to established component-based systems, cloud applications normally entail numerous cloud components that communicate over application programming interface. To attack this crucial challenge, we put forward a personalized ranking prediction structure, named cloud Rank to forecast quality of service ranking concerning a set of cloud services devoid of requiring extra real-world service invocations from the projected users. The target users of cloud rank structure are cloud applications, which require personalized cloud service ranking in support of building selection of optimal service.

Key-Words / Index Term

Cloud Service, Quality Of Service, Cloud Rank, Personalized Service

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