research-article

Towards robust service compositions in the context of functionally diverse services

Authors:

Florian Wagner,

Benjamin Kloepper,

Fuyuki Ishikawa,

Shinichi HonidenAuthors Info & Claims

WWW '12: Proceedings of the 21st international conference on World Wide Web

Pages 969 - 978

https://doi.org/10.1145/2187836.2187966

Published: 16 April 2012 Publication History

Abstract

Web service composition provides a means of customized and flexible integration of service functionalities. Quality-of-Service (QoS) optimization algorithms select services in order to adapt workflows to the non-functional requirements of the user. With increasing number of services in a workflow, previous approaches fail to achieve a sufficient reliability. Moreover, expensive ad-hoc replanning is required to deal with service failures. The major problem with such sequential application of planning and replanning is that it ignores the potential costs during the initial planning and they consequently are hidden from the decision maker. Our basic idea to overcome this substantial problem is to compute a QoS optimized selection of service clusters that includes a sufficient number of backup services for each service employed. To support the human decision maker in the service selection task, our approach considers the possible repair costs directly in the initial composition. On the basis of a multi-objective approach and using a suitable service selection interface, the decision maker can select compositions in line with his/her personal risk preferences.

References

[1]

M. Alrifai and T. Risse. Combining Global Optimization with Local Selection for Efficient QoS-aware Service Composition. In Proceedings of the 18th International Conference on World Wide Web, (WWW), New York, NY, USA, 2009. ACM.

Digital Library

[2]

M. Alrifai, D. Skoutas, and T. Risse. Selecting Skyline Services for QoS-based Web Service Composition. In Proceedings of the 19th International Conference on World Wide Web, (WWW), New York, NY, USA, 2010. ACM.

Digital Library

[3]

B. Benatallah, M. Dumas, Q. Z. Sheng, and A. H. H. Ngu. Declarative composition and peer-to-peer provisioning of dynamic web services. InProceedings of the 18th International Conference on Data Engineering (ICDE), 2002.

Digital Library

[4]

G. Canfora, M. Di Penta, R. Esposito, and M. L. Villani. An Approach for QoS-aware Service Composition based on Genetic Algorithms. In Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO), 2005.

Digital Library

[5]

K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.IEEE Transactions on Evolutionary Computation, 6:182--197, 2002.

Digital Library

[6]

J. J. Durillo and A. J. Nebro. jMetal: A Java Framework for Multi-Objective Optimization. Advances in Engineering Software, 42:760--771, 2011.

Digital Library

[7]

F. Ishikawa, S. Katafuchi, F. Wagner, Y. Fukazawa, and S. Honiden. Bridging the Gap Between Semantic Web Service Composition and Common Implementation Architectures. IEEE International Conference on Services Computing (SCC), 2011.

Digital Library

[8]

M. C. Jaeger and H. Ladner. Improving the QoS of WS Compositions Based on Redundant Services. In Proceedings of the International Conference on Next Generation Web Services Practices (NWESP). IEEE Computer Society, 2005.

Digital Library

[9]

A. Klein, F. Ishikawa, and B. Bauer. A Probabilistic Approach to Service Selection with Conditional Contracts and Usage Patterns. InProceedings of the 7th International Joint Conference on Service-Oriented Computing (ICSOC), Berlin, Heidelberg, 2009. Springer-Verlag.

Digital Library

[10]

S. Kukkonen and J. Lampinen. GDE3: The third Evolution Step of Generalized Differential Evolution. In IEEE Congress on Evolutionary Computation (CEC), 2005.

[11]

N. B. Lakhal, T. Kobayashi, and H. Yokota. A Failure-Aware Model for Estimating and Analyzing the Efficiency of Web Services Compositions. In Proceedings of the Pacific Rim International Symposium on Dependable Computing (PRDC), 2005.

Digital Library

[12]

M. Laukkanen and H. Helin. Composing workflows of semantic web services. InProceedings of the Workshop on Web-Services and Agent-based Engineering, 2003.

[13]

F. Lecue, A. Delteil, and A. Leger. Optimizing Causal Link Based Web Service Composition. In Proceedings of the 18th European Conference on Artificial Intelligence (ECAI), pages 45--49. IOS Press, 2008.

Digital Library

[14]

K.-J. Lin, J. Zhang, and Y. Zhai. An efficient approach for service process reconfiguration in SOA with End-to-End QoS constraints. In B. Hofreiter and H. Werthner, editors,(CEC), pages 146--153. IEEE Computer Society, 2009.

Digital Library

[15]

N. B. Mabrouk, S. Beauche, E. Kuznetsova, N. Georgantas, and V. Issarny. QoS-aware Service Composition in Dynamic Service Oriented Environments. In Proceedings of the 10th ACM/IFIP/USENIX Intl. Conf. on Middleware, 2009.

Digital Library

[16]

S. B. Mokhtar, D. Preuveneers, N. Georgantas, V. Issarny, and Y. Berbers. EASY: Efficient semantic service discovery in pervasive computing environments with QoS and context support.Journal of Systems and Software, 81(5):785--808, 2008.

Digital Library

[17]

J. O'Sullivan, D. Edmond, and A. H. M. ter Hofstede. What's in a Service? Distributed and Parallel Databases, 12(2/3):117--133, 2002.

Digital Library

[18]

M. Reyes and C. Coello Coello. Improving PSO-based Multi-objective Optimization Using Crowding, Mutation and-dominance. In C. Coello, A. Hernandez, and E. Zitler, editors,Third International Conference on Evolutionary MultiCriterion Optimization (EMO), volume 3410 of LNCS, pages 509--519. Springer, 2005.

Digital Library

[19]

H. Wada, P. Champrasert, J. Suzuki, and K. Oba. Multiobjective Optimization of SLA-Aware Service Composition. In Proceedings of the 2008 IEEE Congress on Services - Part I, (SERVICES), Washington, DC, USA, 2008. IEEE Computer Society.

Digital Library

[20]

F. Wagner, F. Ishikawa, and S. Honiden. Achieving Constraint Compliance in QoS-aware Service Planning. In Proceedings of the 2nd Intl. Joint Agent Workshop and Symposium (iJAWS), 2011.

[21]

F. Wagner, F. Ishikawa, and S. Honiden. Applying QoS-aware Service Selection on Functionally Diverse Services. InICSOC Workshop on Non-Functional Properties and SLA Management in Service-Oriented Computing (NFPSLAM-SOC), Lecture Notes in Computer Science, 2011.

Digital Library

[22]

F. Wagner, F. Ishikawa, and S. Honiden. QoS-Aware Automatic Service Composition by Applying Functional Clustering.IEEE International Conference on Web Services (ICWS), 2011.

Digital Library

[23]

J. Wang and Y. Hou. Optimal Web Service Selection based on Multi-Objective Genetic Algorithm. In Proceedings of the 2008 International Symposium on Computational Intelligence and Design (ISCID), Washington, DC, USA, 2008. IEEE Computer Society.

Digital Library

[24]

W. Wiesemann, R. Hochreiter, and D. Kuhn. A Stochastic Programming Approach for QoS-Aware Service Composition. InProceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGRID), pages 226--233, Washington, DC, USA, 2008. IEEE Computer Society.

Digital Library

[25]

L. Zeng, B. Benatallah, M. Dumas, J. Kalagnanam, and Q. Z. Sheng. Quality Driven Web Services Composition. InProceedings of the 12th International Conference on World Wide Web (WWW), 2003.

Digital Library

[26]

E. Zitzler and S. Kunzli. Indicator-based Selection in Multiobjective Search. In Proceedings of the Conference on Parallel Problem Solving from Nature (PPSN), 2004.

[27]

E. Zitzler and L. Thiele. Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study. In Proceedings of the Conference on Parallel Problem Solving from Nature (PPSN), 1998.

Digital Library

Cited By

Ishikawa F(2024)Consistent and Quality-Aware Service Composition in Smart CitiesHuman-Centered Services Computing for Smart Cities10.1007/978-981-97-0779-9_1(3-21)Online publication date: 5-May-2024
https://doi.org/10.1007/978-981-97-0779-9_1
Cui YJia ZLiu YDong RXing X(2023)Multi-Attribute Decision Web Service Selection based on Optimal Ant Colony Algorithm2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)10.1109/DDCLS58216.2023.10166659(141-146)Online publication date: 12-May-2023
https://doi.org/10.1109/DDCLS58216.2023.10166659
Ray KBanerjee AMohalik S(2022)Service Selection With Package Bundles and Compatibility ConstraintsIEEE Transactions on Services Computing10.1109/TSC.2021.307503015:5(3031-3046)Online publication date: 1-Sep-2022
https://doi.org/10.1109/TSC.2021.3075030
Show More Cited By

Index Terms

Towards robust service compositions in the context of functionally diverse services
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing systems and tools
2. Information systems
  1. World Wide Web

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Published In

cover image ACM Other conferences

WWW '12: Proceedings of the 21st international conference on World Wide Web

April 2012

1078 pages

ISBN:9781450312295

DOI:10.1145/2187836

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

Copyright © 2012 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]

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Univ. de Lyon: Universite de Lyon

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

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Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Ishikawa F(2024)Consistent and Quality-Aware Service Composition in Smart CitiesHuman-Centered Services Computing for Smart Cities10.1007/978-981-97-0779-9_1(3-21)Online publication date: 5-May-2024
https://doi.org/10.1007/978-981-97-0779-9_1
Cui YJia ZLiu YDong RXing X(2023)Multi-Attribute Decision Web Service Selection based on Optimal Ant Colony Algorithm2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)10.1109/DDCLS58216.2023.10166659(141-146)Online publication date: 12-May-2023
https://doi.org/10.1109/DDCLS58216.2023.10166659
Ray KBanerjee AMohalik S(2022)Service Selection With Package Bundles and Compatibility ConstraintsIEEE Transactions on Services Computing10.1109/TSC.2021.307503015:5(3031-3046)Online publication date: 1-Sep-2022
https://doi.org/10.1109/TSC.2021.3075030
Wu ZMeng KYan XShi DHu B(2021)Abstraction Refinement Approach for Web Service Selection using Skyline Computations2021 IEEE World Congress on Services (SERVICES)10.1109/SERVICES51467.2021.00038(66-71)Online publication date: Sep-2021
https://doi.org/10.1109/SERVICES51467.2021.00038
Chattopadhyay SBanerjee A(2020)QoS-aware Automatic Web Service Composition with Multiple ObjectivesACM Transactions on the Web10.1145/338914714:3(1-38)Online publication date: 18-May-2020
https://dl.acm.org/doi/10.1145/3389147
Ye DHe QWang YYang Y(2019)An Agent-Based Integrated Self-Evolving Service Composition Approach in Networked EnvironmentsIEEE Transactions on Services Computing10.1109/TSC.2016.263159812:6(880-895)Online publication date: 1-Nov-2019
https://doi.org/10.1109/TSC.2016.2631598
Ray KBanerjee AMohalik S(2019)Web Service Selection with Correlations: A Feature-Based Abstraction Refinement Approach2019 IEEE 12th Conference on Service-Oriented Computing and Applications (SOCA)10.1109/SOCA.2019.00013(33-40)Online publication date: Nov-2019
https://doi.org/10.1109/SOCA.2019.00013
Zhao XLi RZuo X(2019)Advances on QoS‐aware web service selection and composition with nature‐inspired computingCAAI Transactions on Intelligence Technology10.1049/trit.2019.00184:3(159-174)Online publication date: 6-Sep-2019
https://doi.org/10.1049/trit.2019.0018
Wu QZhou MZhu QXia Y(2018)VCG Auction-Based Dynamic Pricing for Multigranularity Service CompositionIEEE Transactions on Automation Science and Engineering10.1109/TASE.2017.269512315:2(796-805)Online publication date: Apr-2018
https://doi.org/10.1109/TASE.2017.2695123
Barakat LMiles SLuck M(2018)Adaptive composition in dynamic service environmentsFuture Generation Computer Systems10.1016/j.future.2016.12.00380:C(215-228)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1016/j.future.2016.12.003
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