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Reseach Article

Genetic Approach for Service Selection problem in Composite Web Service

by N. Sasikaladevi, L. Arockiam
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 4
Year of Publication: 2012
Authors: N. Sasikaladevi, L. Arockiam
10.5120/6252-8396

N. Sasikaladevi, L. Arockiam . Genetic Approach for Service Selection problem in Composite Web Service. International Journal of Computer Applications. 44, 4 ( April 2012), 22-29. DOI=10.5120/6252-8396

@article{ 10.5120/6252-8396,
author = { N. Sasikaladevi, L. Arockiam },
title = { Genetic Approach for Service Selection problem in Composite Web Service },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 4 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 22-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number4/6252-8396/ },
doi = { 10.5120/6252-8396 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:34:41.470588+05:30
%A N. Sasikaladevi
%A L. Arockiam
%T Genetic Approach for Service Selection problem in Composite Web Service
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 4
%P 22-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Services are the basic amass that aims to support the building of business application in a more flexible and interoperable manner for enterprise collaboration. Satisfying the needs of service consumer and to become accustomed to changing needs, service composition is performed to compose the various capabilities of available services. With the proliferation of services presenting similar functionalities around the web, the task of service selection for service composition is intricate. It is vital to provide systematic methodology for selecting required web services according to their non-functional characteristics or quality of service (QoS). Various heuristic and meta-heuristic algorithms are evolving to solve the QoS based service selection problem. One of the meta-heuristic algorithms is genetic algorithm. In this paper, the genetic algorithm is developed to maximize the non-functional Characteristic called the reliability of the composite web service and the performance of the developed algorithm is calculated.

References
  1. M. Sathya, M. Swarnamugi, P. Dhavachelvan, G. Sureshkumar, "Evaluation of QoS based Web- Service Selection Techniques for Service Composition", International Journal of Software Engineering (IJSE) , 2011
  2. Huiyuan Zheng; Jian Yang; Weiliang Zhao; "QoS Analysis and Service Selection for Composite Services" , 2010 IEEE International Conference on Services Computing, pp. 122 – 129, 2010
  3. Ping Wang, Kuo-Ming Chao, Chi-Chun Lo and Ray Farmer, "An evidence-based scheme for web service selection ", Special Issue: Advances in E-Business Engineering, 2010
  4. Matteo Baldon, Cristina Baroglio, Alberto Martelli, Viviana Patti. "Reasoning about interaction protocols for customizing web service selection and composition". The Journal of Logic and Algebraic Programming, Elsevier, No. 70, pp. 53 – 73, 2007.
  5. Shangguang Wang; Zibin Zheng; Qibo Sun; Hua Zou; Fangchun Yang; "Cloud model for service selection", 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 666 – 671, 2011
  6. Xin-She Yang, Engineering Optimization: An Introduction with Metaheuristic Applications, Wiley Publications, 2010.
  7. E. -G. Talbi, Metaheuristics: From Design to Implementation, John Wiley Publications,2009.
  8. Kellerer H, Pferschy and Pisinger, Knapsack Problems, springer-Verlag, 2004
  9. Tao Yu, Yue Zhang, Kwei jay lin,"Efficient Algorithms for Web Services Selection with End-to-End QoS Constraints", ACM Transactions on the Web, Vol. 1, No. 1, Article 6, May 2007.
  10. Yi Xia; Ping Chen; Liang Bao; Meng Wang; Jing Yang; "A QoS-Aware Web Service Selection Algorithm Based on Clustering", 2011 IEEE International Conference on Web Services(ICWS),pp. 428 – 435,2011.
  11. Chao Lv, Wanchun Dou, Jinjun Chen. "QoS-Aware Service Selection Using QDG for B2B Collaboration". In Proceedings of the fourteenth IEEE International Conference on Parallel and Distributed Systems, pp. 336 – 343, 2008.
  12. Mobedpour, D. ; Chen Ding; Chi-Hung Chi; "A QoS Query Language for User-Centric Web Service Selection" , 2010 IEEE International Conference on Services Computing (SCC), pp. 273 – 280, 2010.
  13. Qibo Sun , Shangguang Wang, Hua Zou, Fangchun Yang, "QSSA: A QoS-aware Service Selection Approach", International Journal of Web and Grid Services, Volume 7, Number 2 , pp. 147 - 169 , 2011
  14. Liu Zhi-Zhong; Wang Zhi-Jian; Zhou Xiao-Feng; Lou Yuan-Sheng; Shang Ling; "A New Algorithm for QoS-Aware Composite Web Services Selection", 2nd International Workshop on Intelligent Systems and Applications (ISA), pp. 1 - 4 ,2010
  15. Chengwen Zhang; Beijing, "Adaptive Genetic Algorithm for QoS-aware Service Selection", 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications (WAINA), 273 – 278,2011.
  16. Swarnamugi . M, Sathya . M. "Specification Criteria for Web Service Selection Approaches". International Journal on Computer Engineering and Information Technology, vol( 23), Issue No: 01, pp. 29 – 382010.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm Mmkp Fitness