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QoS-aware Web Service Composition Considering the Constraints between Services

Published: 22 September 2017 Publication History

Abstract

In the field of Web service composition, many scholars consider that there is no connection between concrete services but actually there are conflicts and dependencies between different types of services. For addressing the problem of QoS-aware Web service composition which considers conflicts and dependencies between services, a chaos genetic algorithm (CGA) is proposed. In this paper, chaos theory is used to generate the initial population of the genetic algorithm. As well as the repair strategy is used to deal with the individuals in the initial population that violate different constraints. After selection, crossover and mutation operations, the algorithm may produce infeasible individuals that violate the constraints between services, and hence new fitness function is needed to deal with the issue of that population has infeasible individuals. And then small degree chaotic disturbance is imposed to the population, which can help genetic algorithm to jump out of local optimum and can speed up the convergence. Experimental results demonstrate the effectiveness of the proposed algorithm.

References

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Sun, Y., Tan, W., Li, L., Shen, W., Bi, Z., & Hu, X. 2016. A new method to identify collaborative partners in social service provider networks. Information Systems Frontiers, 18, 3 (2016), 565--578.
[2]
D'Mello, D.A., Ananthanarayana, V.S., & Salian, S. 2011. A review of dynamic web service composition techniques. In International Conference on Computer Science and Information Technology. Springer, Berlin, Heidelberg, 85--97.
[3]
Gao, A., Yang, D., Tang, S., & Zhang, M. 2006. QoS-Driven Web Service Composition with Inter Service Conflicts. Frontiers of WWW Research and Development - APWEB 2006, 121--132.
[4]
Li, Y., & Wen, T. 2009. Quality and Relation Driven Service Selection for Web Services Composition. In New Trends in Information and Service Science(NISS'09). 152--155.
[5]
Ai, L., & Tang, M. 2008. A Penalty-Based Genetic Algorithm for QoS-Aware Web Service Composition with Inter-service Dependencies and Conflicts. International Conference on Computational Intelligence for Modelling Control & Automation, 738--743.
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Ai, L., & Tang, M. 2008. QoS-Based Web Service Composition Accommodating Inter-service Dependencies Using Minimal-Conflict Hill-Climbing Repair Genetic Algorithm. IEEE Fourth International Conference on Escience(Escience). 119--126.
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Wu, Y., & Wang, X. 2011. Applying multi-objective genetic algorithms to qosaware web service global selection. Advances in Information Sciences & Service Sciences, 3, 11 (2011), 473--482.
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Tang, M., & Ai, L. 2010. A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition. IEEE Congress on Evolutionary Computation, 1--8.

Cited By

View all
  • (2024)Hierarchical Service Composition via Blockchain-enabled Federated LearningData Science and Engineering10.1007/s41019-024-00258-7Online publication date: 24-Aug-2024
  • (2022)Coordinate System-Based Trust-Aware Web Services Composition in Edge and Cloud EnvironmentThe Computer Journal10.1093/comjnl/bxac06366:9(2102-2117)Online publication date: 20-May-2022
  • (2021)Method Towards Service Composition Optimization on Cost-effective using Mixed Flower Pollination Algorithm2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD49262.2021.9437795(37-42)Online publication date: 5-May-2021

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    Published In

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    ChineseCSCW '17: Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing
    September 2017
    269 pages
    ISBN:9781450353526
    DOI:10.1145/3127404
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 September 2017

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    Author Tags

    1. Conflict
    2. Genetic Algorithm
    3. QoS-aware
    4. Web service composition
    5. chaos
    6. dependency

    Qualifiers

    • Poster
    • Research
    • Refereed limited

    Funding Sources

    • the Graduate Innovation Program
    • Key Discipline Foundation of Shanghai Second Polytechnic University
    • the Natural Science Foundation of China

    Conference

    ChineseCSCW '17

    Acceptance Rates

    ChineseCSCW '17 Paper Acceptance Rate 21 of 84 submissions, 25%;
    Overall Acceptance Rate 21 of 84 submissions, 25%

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    Cited By

    View all
    • (2024)Hierarchical Service Composition via Blockchain-enabled Federated LearningData Science and Engineering10.1007/s41019-024-00258-7Online publication date: 24-Aug-2024
    • (2022)Coordinate System-Based Trust-Aware Web Services Composition in Edge and Cloud EnvironmentThe Computer Journal10.1093/comjnl/bxac06366:9(2102-2117)Online publication date: 20-May-2022
    • (2021)Method Towards Service Composition Optimization on Cost-effective using Mixed Flower Pollination Algorithm2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD49262.2021.9437795(37-42)Online publication date: 5-May-2021
    • (2021)Optimization of Business Process Execution in Services Architecture: A Systematic Literature ReviewIEEE Access10.1109/ACCESS.2021.31026689(111833-111852)Online publication date: 2021

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