CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

SFL Algorithm for QoS-based Cloud Service Composition

by Ali Younes, Mohamed Essaaidi, Ahmed El Moussaoui
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 97 - Number 17
Year of Publication: 2014
Authors: Ali Younes, Mohamed Essaaidi, Ahmed El Moussaoui
10.5120/17103-7700

Ali Younes, Mohamed Essaaidi, Ahmed El Moussaoui . SFL Algorithm for QoS-based Cloud Service Composition. International Journal of Computer Applications. 97, 17 ( July 2014), 42-49. DOI=10.5120/17103-7700

@article{ 10.5120/17103-7700,
author = { Ali Younes, Mohamed Essaaidi, Ahmed El Moussaoui },
title = { SFL Algorithm for QoS-based Cloud Service Composition },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 97 },
number = { 17 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 42-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume97/number17/17103-7700/ },
doi = { 10.5120/17103-7700 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:24:25.290660+05:30
%A Ali Younes
%A Mohamed Essaaidi
%A Ahmed El Moussaoui
%T SFL Algorithm for QoS-based Cloud Service Composition
%J International Journal of Computer Applications
%@ 0975-8887
%V 97
%N 17
%P 42-49
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the advent of cloud service-based applications and Software as a Service (SaaS), new applications have recently known an increasing use of service-oriented architecture (SOA). This model has allowed computer science and associated industries to build new customized applications, by using the available and the existing cloud services bridged together dynamically to form a complex workflow process with more functionalities. However cloud services with similar and compatible functionalities may be offered by multiple providers but may also be offered at different QoS levels. Hence, to build a composite service with a high QoS, a decision should be made based on end-to-end QoS. This work proposes a new approach, for QoS-aware cloud service composition, which addresses a universal model, with end-to-end QoS. It also proposes an effective evolutionary method based on Shuffled Frog Leaping Algorithm (SFLA), which is satisfying global and local constraints. Therefore, in order to evaluate the robustness of the proposed approach, we have evaluated the impact of several parameters that are highly significant in evolutionary methods, such as the impact of the population size, number of candidate services per task and number of criteria. The experimental results show that the chosen algorithm performs better than the ones based on Genetic Algorithm (GA).

References
  1. L. Min, Z. Liang-Jie, and L. Fengyun, "An Insuanrance Model for Guaranteeing Service Assurance, Integrity and QoS in Cloud Computing," Proceedings of the 8th IEEE International Conference Web Services (ICWS 2010), 2010, pp. 584-591.
  2. A. Younes, M. Essaaidi, A. El Moussaoui, A. Bendahmane, "Grid computing middleware information systems: Review and synthesis study", in International Conference on Multimedia Computing and Systems, 2009. ICMCS '09, 2-4 April 2009.
  3. S. Distefano, A. Pulia?to, M. Rak and S. Venticinque, "QoS Management in Cloud @ Home Infrastructures", International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, IEEE (2011).
  4. O. Kayed Qtaish, Z. BtJamaludin, M. Mahmuddin, "Multi-Path QoS-Aware Service Composition", International Journal of Engineering Research and Applications (IJERA), ISSN: 2248-9622, Vol. 2, Issue 2, Mar-Apr 2012, pp. 1075-1085.
  5. Min Liu, Mingrui Wang, Weiming Shen,Nan Luo, Junwei Yan, "A quality of service (QoS)-aware execution plan selection approach for a service composition process", Future Generation Computer Systems, 28 (2012) 1080–1089
  6. Yu, T. , Zhang, Y. , and Lin, K. -J. 2007. "Ef?cient algorithms for Web services selection with end-to-end QoS constraints", ACM Trans. Web 1, 1, Article 6 (May 2007),
  7. M. AllamehAmiri, V. Derhami, M. Ghasemzadeh, "QoS-Based web service composition based on genetic algorithm", Journal of AI and Data Mining, Vol. 1, No. 2, 2013, 63-73
  8. ISO8402: Quality management and quality assurance vocabulary, 1994.
  9. ITU-T Recommendation E. 800, Terms and Definitions Related to Quality of Service and Network Performance Including Dependability, 09/2008.
  10. F. lecue, A. delteil, A. leger, "Optimizing causal link based Web service composition ", in ECAI, 2008 45-49
  11. HUANG, A. F. M. , C. W. LAN, S. J. H. YANG, "An Optimal Qos-Based Web Service Selection Scheme", Systems and Software, Vol 81, (2008), pp. 2079–2090.
  12. A. Younes, M. Essaaid,A. ElMoussaoui, A. Bendahmane, "A fuzzy MADM approach for grid services composition," Multimedia Computing and Systems (ICMCS), 2011 International Conference, ICMCS. 2011
  13. M. Eusuff and K. Lansey, "Optimization of water distribution network design using the shuffled frog leaping algorithm," Journal of Water Resources Planning and Management, vol. 129, no. 3, pp. 210–225, 2003
  14. M. Alrifai, D. Skoutas, T. Risse, "Selecting skyline services for QoS-based web service composition", in WWW 2010, pp 11-20
  15. Y. Zongkai, S. Chaowang,L. Qingtang, Z. Chengling,"A Dynamic Web Services Composition Algorithm Based on the Combination of Ant Colony Algorithm and Genetic Algorithm", Journal of Computational Information Systems, 6:8(2010) 2617-2622.
  16. M. Jaeger and G. Muhl. "QoS-Based Selection of Services: The Implementation of a Genetic Algorithm", In KiVS 2007 Workshop: Service-Oriented Architectures und Service-Oriented Computing (SOA/SOC), Bern, Switzerland, pages 359{370, 2007
  17. FERCHICHI, S. E, K. LAABIDI, S. ZIDI, "Genetic Algorithm and tabu Search for Feature Selection", Studies in Informations and Control, Vol. 18, No. 2, (2009)
  18. R. Wang, C. -H. Chi, and J. Deng, "A Fast Heuristic Algorithm for the Composite Web Service Selection", Advances in Data and Web Management, 5446 (Heidelberg: Springer Berlin 2009) 506-518.
  19. A. Klein, F. Ishikawa, and S. Honiden. "Efficient, Heuristic Approach with Improved Time Complexityfor QoS-aware Service Composition", In IEEE, International Conference on Web Services (ICWS 2011), pages 436{443, 2011.
  20. Ravi Khadka, Bramhananda Sapkota, Luís Ferreira Pires, Marten van Sinderen, Slinger Jansen, Model-driven approach to enterprise interoperability at the technical service level, Computers in Industry, Volume 64, Issue 8, October 2013, Pages 951-965.
  21. Xue-hui, YANG Ye, LI Xia ,"Solving TSP with Shuffled Frog-Leaping Algorithm", Eighth International Conference on Intelligent Systems Design and Applications , ISDA, Kaohsiung, Taiwan, November 26-28, 2008 ( ISBN: 978-0-7695-3382-7).
  22. Antariksha Bhaduri, "A Clonal Selection Based Shuffled Frog Leaping Algorithm", 4th Annual IEEE Conference. International Advance Computing Conference, IACC, Patiala, India, March 2009 (ISBN: 978-1-4244-2927-1).
  23. Haifeng Li, Qing Z, Xiaoxia Y, Linrong X, "Geo-information processing service composition for concurrent tasks: A QoS-aware game theory approach", Computers & Geosciences, 47, (2012) 46-56.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud services composition QoS optimization SFLA GA.

Powered by PhDFocusTM