research-article

Top-k service compositions: a fuzzy set-based approach

Authors:

Karim Benouaret,

Djamal Benslimane,

Allel HadjaliAuthors Info & Claims

SAC '11: Proceedings of the 2011 ACM Symposium on Applied Computing

Pages 1033 - 1038

https://doi.org/10.1145/1982185.1982412

Published: 21 March 2011 Publication History

Abstract

Data as a Service (DaaS) is a flexible way that allows enterprises to expose their data. Composition of DaaS services provides bridges to answer queries. User preferences are becoming increasingly important to personalizing the composition process. In this paper, we propose an approach to compose DaaS services in the context of preference queries where preferences are modeled by means of fuzzy sets that allow for a large variety of flexible terms such as 'cheap', 'affordable' and 'fairly expensive'. The proposed approach is based on RDF-based query rewritings to take into account the partial matching between individual DaaS services and parts of the user query. Matching degrees between DaaS services and fuzzy preference constraints are computed by means of different constraints inclusion methods. Such degrees express to which extent a service is relevant to the resolution of the query. A fuzzification of Pareto dominance is also proposed to better rank composite services by computing the score of services. The resulting scores are then used to compute the top-k DaaS service compositions that cover the user query.

References

[1]

W. Bandler and L. kohout. Fuzzy power and fuzzy implication operators. Fuzzy Sets and Systems, 4: 13--30, 1980.

[2]

M. Barhamgi, D. Benslimane, and B. Medjahed. A query rewriting approach for web service composition. IEEE Transactions on Services Computing (TSC), 15(5): 795--825, jan 2010.

Digital Library

[3]

S. Borzsonyi, D. Kossmann, and K. Stocker. The skyline operator. In IEEE International Conference on Data Engineering, ICDE 2001, pages 421--430, 2001.

Digital Library

[4]

D. Butler. Mashups mix data into global service. Nature, 2006.

[5]

M. Carey. This is your data on soa. In In IEEE Int. Conference on Services-Oriented Computing and Applications, 2007.

Digital Library

[6]

D. Dubois and H. Prade. Fundamentals of fuzzy sets, volume 7 of The Handbooks of Fuzzy Sets. Kluwer Academic Pub, Netherlands, 2000.

[7]

A. Jhingran. Enterprise information mashups: integrating information, simply. In In Proccedings of the 2006 VLDB, pages 3--4, 2006.

Digital Library

[8]

M. Koppen and R. Vicente Garcia. A fuzzy scheme for teh ranking of multivariate data and its application. In In Proccedings of the 2004 Annual Meeting of the NAFIPS, pages 140--145, 2004.

[9]

M. Palmonari, M. Comerio, and F. De Paoli. Effective and flexible nfp-based ranking of web services. In ICSOC-ServiceWave '09, pages 546--560, Berlin, Heidelberg, 2009. Springer-Verlag.

Digital Library

[10]

J. Pei, B. Jiang, X. Lin, and Y. Yuan. Probabilistic skylines on uncertain data. In In Proccedings of the 2007 VLDB Conference, pages 20--27, 2007.

Digital Library

[11]

D. Skoutas, D. Sacharidis, A. Simitsis, V. Kantere, and T. K. Sellis. Top-k dominant web services under multi-criteria matching. In EDBT, pages 898--909, 2009.

Digital Library

[12]

H. Wang, J. Xu, and P. Li. Incomplete preference-driven web service selection. In SCC '08: Proceedings of the 2008 IEEE International Conference on Services Computing, pages 75--82, Washington, DC, USA, 2008. IEEE Computer Society.

Digital Library

[13]

Q. Wu, A. Iyengar, R. Subramanian, I. Rouvellou, I. Silva-Lepe, and T. Mikalsen. Combining quality of service and social information for ranking services. In ICSOC-ServiceWave '09, pages 561--575, Berlin, Heidelberg, 2009.

Digital Library

[14]

Q. Yu and A. Bouguettaya. Computing service skyline from uncertain qows. IEEE T. Services Computing, 3(1): 16--29, 2010.

Digital Library

[15]

L. Zadeh. A computational approach to fuzzy quantifiers in natural languages. Computer Mathematics with Applications, 9: 149--183, 1983.

Cited By

Kallab LChbeir RMrissa M(2021)Location-Aware Resource Discovery and QoR-Driven Resource Selection for Hybrid Web EnvironmentsSensors10.3390/s2120683521:20(6835)Online publication date: 14-Oct-2021
https://doi.org/10.3390/s21206835
Kallab LChbeir RMrissa M(2021)QoR-Driven Resource Selection for Hybrid Web EnvironmentsNext-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future10.1007/978-3-030-73203-5_15(189-202)Online publication date: 10-Apr-2021
https://doi.org/10.1007/978-3-030-73203-5_15
Halfaoui AHadjila FDidi F(2015)QoS-Aware Web Services Selection Based on Fuzzy DominanceComputer Science and Its Applications10.1007/978-3-319-19578-0_24(291-300)Online publication date: 2015
https://doi.org/10.1007/978-3-319-19578-0_24
Show More Cited By

Index Terms

Top-k service compositions: a fuzzy set-based approach
1. Information systems
  1. Information retrieval
  2. World Wide Web
    1. Web applications
    2. Web services

Recommendations

A fuzzy framework for selecting top-k web service compositions

Data Web services allow users to access information provided by different companies. Web users often need to compose different Web services to achieve a more complex task that can not be fulfilled by an individual Web service. In addition, user ...
Quality of Service Management for Web Service Compositions
CSE '08: Proceedings of the 2008 11th IEEE International Conference on Computational Science and Engineering

Typically, scientific applications have to be distributed across computational grid infrastructures. These applications can use existent grid services. Service components in this kind of application may have different computational platforms that should ...
Fuzzy rule based web service composition in cloud
DATA '18: Proceedings of the First International Conference on Data Science, E-learning and Information Systems

Cloud Computing has drawn much attention in industry due its efficient cost schema along with more prospects such as elasticity and scalability nature of Cloud Computing. One of the main service model of Cloud is Software as Service, where many Web ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SAC '11: Proceedings of the 2011 ACM Symposium on Applied Computing

March 2011

1868 pages

ISBN:9781450301138

DOI:10.1145/1982185

Conference Chairs:
William Chu
Tunghai University, TaiChung, Taiwan
,
W. Eric Wong
University of Texas at Dallas, Richardson, Texas
,
Program Chairs:
Mathew J. Palakal
Indiana University Purdue University, Indianapolis
,
Chih-Cheng Hung
Southern Polytechnic State University, Marietta

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 March 2011

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Agence Nationale de la Recherche

Conference

SAC'11

Sponsor:

SIGAPP

SAC'11: The 2011 ACM Symposium on Applied Computing

March 21 - 24, 2011

TaiChung, Taiwan

Acceptance Rates

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

Upcoming Conference

SAC '25

Sponsor:
sigapp

The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
211
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 23 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kallab LChbeir RMrissa M(2021)Location-Aware Resource Discovery and QoR-Driven Resource Selection for Hybrid Web EnvironmentsSensors10.3390/s2120683521:20(6835)Online publication date: 14-Oct-2021
https://doi.org/10.3390/s21206835
Kallab LChbeir RMrissa M(2021)QoR-Driven Resource Selection for Hybrid Web EnvironmentsNext-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future10.1007/978-3-030-73203-5_15(189-202)Online publication date: 10-Apr-2021
https://doi.org/10.1007/978-3-030-73203-5_15
Halfaoui AHadjila FDidi F(2015)QoS-Aware Web Services Selection Based on Fuzzy DominanceComputer Science and Its Applications10.1007/978-3-319-19578-0_24(291-300)Online publication date: 2015
https://doi.org/10.1007/978-3-319-19578-0_24
Benouaret KBenslimane DHadjali ABarhamgi MMaamar ZSheng Q(2014)Web Service Compositions with Fuzzy PreferencesACM Transactions on Internet Technology10.1145/257623113:4(1-33)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.1145/2576231
Benouaret KBenslimane DHadjali ABarhamgi M(2011)FuDoCSProceedings of the VLDB Endowment10.14778/3402755.34027884:12(1430-1433)Online publication date: 1-Aug-2011
https://dl.acm.org/doi/10.14778/3402755.3402788
Benouaret KBenslimane DHadjali A(2011)A fuzzy framework for selecting top-k web service compositionsACM SIGAPP Applied Computing Review10.1145/2034594.203459711:3(32-40)Online publication date: 1-Aug-2011
https://dl.acm.org/doi/10.1145/2034594.2034597
Benouaret KBenslimane DHadjali A(2011)On the Use of Fuzzy Dominance for Computing Service Skyline Based on QoSProceedings of the 2011 IEEE International Conference on Web Services10.1109/ICWS.2011.93(540-547)Online publication date: 4-Jul-2011
https://dl.acm.org/doi/10.1109/ICWS.2011.93

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents