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QoS Ranking Prediction Approach for Cloud Services Using Spearman Rank Correlation Based Nature Inspired Firefly Optimization

S. Beghin Bose1 , S.S. Sujatha2

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-04 , Page no. 102-106, Feb-2019

Online published on Feb 28, 2019

Copyright © S. Beghin Bose, S.S. Sujatha . 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: S. Beghin Bose, S.S. Sujatha, “QoS Ranking Prediction Approach for Cloud Services Using Spearman Rank Correlation Based Nature Inspired Firefly Optimization,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.102-106, 2019.

MLA Style Citation: S. Beghin Bose, S.S. Sujatha "QoS Ranking Prediction Approach for Cloud Services Using Spearman Rank Correlation Based Nature Inspired Firefly Optimization." International Journal of Computer Sciences and Engineering 07.04 (2019): 102-106.

APA Style Citation: S. Beghin Bose, S.S. Sujatha, (2019). QoS Ranking Prediction Approach for Cloud Services Using Spearman Rank Correlation Based Nature Inspired Firefly Optimization. International Journal of Computer Sciences and Engineering, 07(04), 102-106.

BibTex Style Citation:
@article{Bose_2019,
author = {S. Beghin Bose, S.S. Sujatha},
title = {QoS Ranking Prediction Approach for Cloud Services Using Spearman Rank Correlation Based Nature Inspired Firefly Optimization},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {07},
Issue = {04},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {102-106},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=730},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=730
TI - QoS Ranking Prediction Approach for Cloud Services Using Spearman Rank Correlation Based Nature Inspired Firefly Optimization
T2 - International Journal of Computer Sciences and Engineering
AU - S. Beghin Bose, S.S. Sujatha
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 102-106
IS - 04
VL - 07
SN - 2347-2693
ER -

           

Abstract

QoS (Quality of Services) is a very important research topic in cloud computing. When we select an optimal cloud service from functionally equivalent service we use QoS value for a good decision making. QoS ranking provides priceless information in selecting the best cloud service in cloud computing. In order to avoid time consumption and to select the best service for the cloud customer a good QoS ranking prediction framework is required. It should be a much user as friendly and less time consuming. In this paper Spearman Rank Correlation Based Nature Inspired Firefly Optimization (SRC-NIFO) method is analyzed for ranking prediction. It will give higher accuracy and be less time consuming. When the proposed framework is compared with the previous works on the basics of response in time, throughput, and latency the proposed work is proved to be much better than the previous works.

Key-Words / Index Term

Cloud computing, quality of service (QoS), Cloud Service Provider, Ranking Prediction, Rank Correlation, Selection.

References

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